Overview

Dataset statistics

Number of variables33
Number of observations10324
Missing cells2383
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory257.0 B

Variable types

Numeric7
Categorical25
Boolean1

Alerts

project code has a high cardinality: 142 distinct values High cardinality
pq # has a high cardinality: 1237 distinct values High cardinality
po / so # has a high cardinality: 6233 distinct values High cardinality
asn/dn # has a high cardinality: 7030 distinct values High cardinality
pq first sent to client date has a high cardinality: 765 distinct values High cardinality
po sent to vendor date has a high cardinality: 897 distinct values High cardinality
scheduled delivery date has a high cardinality: 2006 distinct values High cardinality
delivered to client date has a high cardinality: 2093 distinct values High cardinality
delivery recorded date has a high cardinality: 2042 distinct values High cardinality
vendor has a high cardinality: 73 distinct values High cardinality
item description has a high cardinality: 184 distinct values High cardinality
molecule/test type has a high cardinality: 86 distinct values High cardinality
dosage has a high cardinality: 54 distinct values High cardinality
manufacturing site has a high cardinality: 88 distinct values High cardinality
weight (kilograms) has a high cardinality: 4688 distinct values High cardinality
freight cost (usd) has a high cardinality: 6733 distinct values High cardinality
line item quantity is highly correlated with line item value and 1 other fieldsHigh correlation
line item value is highly correlated with line item quantity and 1 other fieldsHigh correlation
pack price is highly correlated with unit priceHigh correlation
unit price is highly correlated with pack priceHigh correlation
line item insurance (usd) is highly correlated with line item quantity and 1 other fieldsHigh correlation
line item quantity is highly correlated with line item value and 1 other fieldsHigh correlation
line item value is highly correlated with line item quantity and 1 other fieldsHigh correlation
line item insurance (usd) is highly correlated with line item quantity and 1 other fieldsHigh correlation
line item quantity is highly correlated with line item value and 1 other fieldsHigh correlation
line item value is highly correlated with line item quantity and 1 other fieldsHigh correlation
pack price is highly correlated with unit priceHigh correlation
unit price is highly correlated with pack priceHigh correlation
line item insurance (usd) is highly correlated with line item quantity and 1 other fieldsHigh correlation
vendor is highly correlated with manufacturing site and 6 other fieldsHigh correlation
shipment mode is highly correlated with countryHigh correlation
dosage form is highly correlated with manufacturing site and 5 other fieldsHigh correlation
manufacturing site is highly correlated with vendor and 6 other fieldsHigh correlation
vendor inco term is highly correlated with vendor and 1 other fieldsHigh correlation
sub classification is highly correlated with vendor and 6 other fieldsHigh correlation
brand is highly correlated with vendor and 7 other fieldsHigh correlation
fulfill via is highly correlated with vendor and 5 other fieldsHigh correlation
molecule/test type is highly correlated with vendor and 7 other fieldsHigh correlation
dosage is highly correlated with dosage form and 4 other fieldsHigh correlation
country is highly correlated with shipment mode and 1 other fieldsHigh correlation
product group is highly correlated with vendor and 6 other fieldsHigh correlation
id is highly correlated with country and 6 other fieldsHigh correlation
country is highly correlated with id and 11 other fieldsHigh correlation
managed by is highly correlated with vendor and 1 other fieldsHigh correlation
fulfill via is highly correlated with id and 10 other fieldsHigh correlation
vendor inco term is highly correlated with id and 9 other fieldsHigh correlation
shipment mode is highly correlated with country and 4 other fieldsHigh correlation
product group is highly correlated with country and 8 other fieldsHigh correlation
sub classification is highly correlated with country and 9 other fieldsHigh correlation
vendor is highly correlated with id and 15 other fieldsHigh correlation
molecule/test type is highly correlated with id and 14 other fieldsHigh correlation
brand is highly correlated with id and 13 other fieldsHigh correlation
dosage is highly correlated with country and 10 other fieldsHigh correlation
dosage form is highly correlated with country and 10 other fieldsHigh correlation
unit of measure (per pack) is highly correlated with product group and 7 other fieldsHigh correlation
line item quantity is highly correlated with line item value and 1 other fieldsHigh correlation
line item value is highly correlated with line item quantity and 1 other fieldsHigh correlation
pack price is highly correlated with vendor and 3 other fieldsHigh correlation
unit price is highly correlated with vendor and 3 other fieldsHigh correlation
manufacturing site is highly correlated with id and 14 other fieldsHigh correlation
line item insurance (usd) is highly correlated with line item quantity and 1 other fieldsHigh correlation
shipment mode has 360 (3.5%) missing values Missing
dosage has 1736 (16.8%) missing values Missing
line item insurance (usd) has 287 (2.8%) missing values Missing
unit price is highly skewed (γ1 = 40.58484939) Skewed
id has unique values Unique

Reproduction

Analysis started2022-09-29 15:27:43.542807
Analysis finished2022-09-29 15:28:04.486913
Duration20.94 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct10324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51098.96823
Minimum1
Maximum86823
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2022-09-29T11:28:04.589001image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5151.2
Q112795.75
median57540.5
Q383648.25
95-th percentile86167.85
Maximum86823
Range86822
Interquartile range (IQR)70852.5

Descriptive statistics

Standard deviation31944.3325
Coefficient of variation (CV)0.6251463308
Kurtosis-1.639837204
Mean51098.96823
Median Absolute Deviation (MAD)27404
Skewness-0.2303667089
Sum527545748
Variance1020440379
MonotonicityNot monotonic
2022-09-29T11:28:04.873281image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
825651
 
< 0.1%
825941
 
< 0.1%
825951
 
< 0.1%
825961
 
< 0.1%
825971
 
< 0.1%
825991
 
< 0.1%
826001
 
< 0.1%
826011
 
< 0.1%
826021
 
< 0.1%
Other values (10314)10314
99.9%
ValueCountFrequency (%)
11
< 0.1%
31
< 0.1%
41
< 0.1%
151
< 0.1%
161
< 0.1%
231
< 0.1%
441
< 0.1%
451
< 0.1%
461
< 0.1%
471
< 0.1%
ValueCountFrequency (%)
868231
< 0.1%
868221
< 0.1%
868211
< 0.1%
868191
< 0.1%
868181
< 0.1%
868171
< 0.1%
868161
< 0.1%
868151
< 0.1%
868141
< 0.1%
868131
< 0.1%

project code
Categorical

HIGH CARDINALITY

Distinct142
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
116-ZA-T30
768 
104-CI-T30
729 
151-NG-T30
 
628
114-UG-T30
 
596
108-VN-T30
 
522
Other values (137)
7081 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters103240
Distinct characters35
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)0.1%

Sample

1st row100-CI-T01
2nd row108-VN-T01
3rd row100-CI-T01
4th row108-VN-T01
5th row108-VN-T01

Common Values

ValueCountFrequency (%)
116-ZA-T30768
 
7.4%
104-CI-T30729
 
7.1%
151-NG-T30628
 
6.1%
114-UG-T30596
 
5.8%
108-VN-T30522
 
5.1%
106-HT-T30450
 
4.4%
111-MZ-T30431
 
4.2%
110-ZM-T30406
 
3.9%
109-TZ-T30369
 
3.6%
107-RW-T30340
 
3.3%
Other values (132)5085
49.3%

Length

2022-09-29T11:28:05.003899image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
116-za-t30768
 
7.4%
104-ci-t30729
 
7.1%
151-ng-t30628
 
6.1%
114-ug-t30596
 
5.8%
108-vn-t30522
 
5.1%
106-ht-t30450
 
4.4%
111-mz-t30431
 
4.2%
110-zm-t30406
 
3.9%
109-tz-t30369
 
3.6%
107-rw-t30340
 
3.3%
Other values (132)5085
49.3%

Most occurring characters

ValueCountFrequency (%)
-20648
20.0%
118694
18.1%
016409
15.9%
T11732
11.4%
38596
8.3%
Z3815
 
3.7%
G2289
 
2.2%
62032
 
2.0%
N1981
 
1.9%
41852
 
1.8%
Other values (25)15192
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number51609
50.0%
Uppercase Letter30983
30.0%
Dash Punctuation20648
20.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T11732
37.9%
Z3815
 
12.3%
G2289
 
7.4%
N1981
 
6.4%
A1522
 
4.9%
C1490
 
4.8%
M1419
 
4.6%
I1181
 
3.8%
W1053
 
3.4%
U779
 
2.5%
Other values (14)3722
 
12.0%
Decimal Number
ValueCountFrequency (%)
118694
36.2%
016409
31.8%
38596
16.7%
62032
 
3.9%
41852
 
3.6%
51070
 
2.1%
2859
 
1.7%
9740
 
1.4%
8698
 
1.4%
7659
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
-20648
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common72257
70.0%
Latin30983
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T11732
37.9%
Z3815
 
12.3%
G2289
 
7.4%
N1981
 
6.4%
A1522
 
4.9%
C1490
 
4.8%
M1419
 
4.6%
I1181
 
3.8%
W1053
 
3.4%
U779
 
2.5%
Other values (14)3722
 
12.0%
Common
ValueCountFrequency (%)
-20648
28.6%
118694
25.9%
016409
22.7%
38596
11.9%
62032
 
2.8%
41852
 
2.6%
51070
 
1.5%
2859
 
1.2%
9740
 
1.0%
8698
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII103240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-20648
20.0%
118694
18.1%
016409
15.9%
T11732
11.4%
38596
8.3%
Z3815
 
3.7%
G2289
 
2.2%
62032
 
2.0%
N1981
 
1.9%
41852
 
1.8%
Other values (25)15192
14.7%

pq #
Categorical

HIGH CARDINALITY

Distinct1237
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Pre-PQ Process
2681 
FPQ-14942
 
205
FPQ-12522
 
154
FPQ-13973
 
110
FPQ-4537
 
98
Other values (1232)
7076 

Length

Max length14
Median length9
Mean length9.946822937
Min length8

Characters and Unicode

Total characters102691
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique380 ?
Unique (%)3.7%

Sample

1st rowPre-PQ Process
2nd rowPre-PQ Process
3rd rowPre-PQ Process
4th rowPre-PQ Process
5th rowPre-PQ Process

Common Values

ValueCountFrequency (%)
Pre-PQ Process2681
26.0%
FPQ-14942205
 
2.0%
FPQ-12522154
 
1.5%
FPQ-13973110
 
1.1%
FPQ-453798
 
0.9%
FPQ-884090
 
0.9%
FPQ-530378
 
0.8%
FPQ-717578
 
0.8%
FPQ-626275
 
0.7%
FPQ-502370
 
0.7%
Other values (1227)6685
64.8%

Length

2022-09-29T11:28:05.107613image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pre-pq2681
 
20.6%
process2681
 
20.6%
fpq-14942205
 
1.6%
fpq-12522154
 
1.2%
fpq-13973110
 
0.8%
fpq-453798
 
0.8%
fpq-884090
 
0.7%
fpq-717578
 
0.6%
fpq-530378
 
0.6%
fpq-626275
 
0.6%
Other values (1228)6755
51.9%

Most occurring characters

ValueCountFrequency (%)
P15686
15.3%
Q10324
 
10.1%
-10324
 
10.1%
F7643
 
7.4%
16503
 
6.3%
s5362
 
5.2%
e5362
 
5.2%
r5362
 
5.2%
23851
 
3.8%
43824
 
3.7%
Other values (10)28450
27.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number34585
33.7%
Uppercase Letter33653
32.8%
Lowercase Letter21448
20.9%
Dash Punctuation10324
 
10.1%
Space Separator2681
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
16503
18.8%
23851
11.1%
43824
11.1%
53412
9.9%
33326
9.6%
62890
8.4%
02787
8.1%
92745
7.9%
82712
7.8%
72535
 
7.3%
Lowercase Letter
ValueCountFrequency (%)
s5362
25.0%
e5362
25.0%
r5362
25.0%
o2681
12.5%
c2681
12.5%
Uppercase Letter
ValueCountFrequency (%)
P15686
46.6%
Q10324
30.7%
F7643
22.7%
Dash Punctuation
ValueCountFrequency (%)
-10324
100.0%
Space Separator
ValueCountFrequency (%)
2681
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin55101
53.7%
Common47590
46.3%

Most frequent character per script

Common
ValueCountFrequency (%)
-10324
21.7%
16503
13.7%
23851
 
8.1%
43824
 
8.0%
53412
 
7.2%
33326
 
7.0%
62890
 
6.1%
02787
 
5.9%
92745
 
5.8%
82712
 
5.7%
Other values (2)5216
11.0%
Latin
ValueCountFrequency (%)
P15686
28.5%
Q10324
18.7%
F7643
13.9%
s5362
 
9.7%
e5362
 
9.7%
r5362
 
9.7%
o2681
 
4.9%
c2681
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII102691
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P15686
15.3%
Q10324
 
10.1%
-10324
 
10.1%
F7643
 
7.4%
16503
 
6.3%
s5362
 
5.2%
e5362
 
5.2%
r5362
 
5.2%
23851
 
3.8%
43824
 
3.7%
Other values (10)28450
27.7%

po / so #
Categorical

HIGH CARDINALITY

Distinct6233
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
SCMS-199289
 
67
SCMS-199283
 
63
SCMS-183950
 
55
SCMS-259075
 
38
SCMS-215370
 
38
Other values (6228)
10063 

Length

Max length11
Median length10
Mean length9.056567222
Min length6

Characters and Unicode

Total characters93500
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4540 ?
Unique (%)44.0%

Sample

1st rowSCMS-4
2nd rowSCMS-13
3rd rowSCMS-20
4th rowSCMS-78
5th rowSCMS-81

Common Values

ValueCountFrequency (%)
SCMS-19928967
 
0.6%
SCMS-19928363
 
0.6%
SCMS-18395055
 
0.5%
SCMS-25907538
 
0.4%
SCMS-21537038
 
0.4%
SCMS-25907933
 
0.3%
SCMS-2350026
 
0.3%
SCMS-21541026
 
0.3%
SCMS-25907820
 
0.2%
SCMS-16244020
 
0.2%
Other values (6223)9938
96.3%

Length

2022-09-29T11:28:05.214329image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scms-19928967
 
0.6%
scms-19928363
 
0.6%
scms-18395055
 
0.5%
scms-25907538
 
0.4%
scms-21537038
 
0.4%
scms-25907933
 
0.3%
scms-2350026
 
0.3%
scms-21541026
 
0.3%
scms-25907820
 
0.2%
scms-16244020
 
0.2%
Other values (6223)9938
96.3%

Most occurring characters

ValueCountFrequency (%)
S15243
16.3%
-10324
11.0%
010280
11.0%
16433
 
6.9%
46052
 
6.5%
25714
 
6.1%
35482
 
5.9%
O5404
 
5.8%
C4920
 
5.3%
M4920
 
5.3%
Other values (6)18728
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number52688
56.4%
Uppercase Letter30488
32.6%
Dash Punctuation10324
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
010280
19.5%
16433
12.2%
46052
11.5%
25714
10.8%
35482
10.4%
54241
8.0%
83850
 
7.3%
73657
 
6.9%
93634
 
6.9%
63345
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
S15243
50.0%
O5404
 
17.7%
C4920
 
16.1%
M4920
 
16.1%
D1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
-10324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common63012
67.4%
Latin30488
32.6%

Most frequent character per script

Common
ValueCountFrequency (%)
-10324
16.4%
010280
16.3%
16433
10.2%
46052
9.6%
25714
9.1%
35482
8.7%
54241
6.7%
83850
 
6.1%
73657
 
5.8%
93634
 
5.8%
Latin
ValueCountFrequency (%)
S15243
50.0%
O5404
 
17.7%
C4920
 
16.1%
M4920
 
16.1%
D1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII93500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S15243
16.3%
-10324
11.0%
010280
11.0%
16433
 
6.9%
46052
 
6.5%
25714
 
6.1%
35482
 
5.9%
O5404
 
5.8%
C4920
 
5.3%
M4920
 
5.3%
Other values (6)18728
20.0%

asn/dn #
Categorical

HIGH CARDINALITY

Distinct7030
Distinct (%)68.1%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
ASN-19166
 
54
ASN-24415
 
38
ASN-23875
 
26
ASN-32138
 
19
ASN-28036
 
17
Other values (7025)
10170 

Length

Max length9
Median length8
Mean length7.627179388
Min length4

Characters and Unicode

Total characters78743
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5580 ?
Unique (%)54.0%

Sample

1st rowASN-8
2nd rowASN-85
3rd rowASN-14
4th rowASN-50
5th rowASN-55

Common Values

ValueCountFrequency (%)
ASN-1916654
 
0.5%
ASN-2441538
 
0.4%
ASN-2387526
 
0.3%
ASN-3213819
 
0.2%
ASN-2803617
 
0.2%
ASN-2803417
 
0.2%
DN-30417
 
0.2%
ASN-2803317
 
0.2%
ASN-3079217
 
0.2%
ASN-737316
 
0.2%
Other values (7020)10086
97.7%

Length

2022-09-29T11:28:05.309073image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asn-1916654
 
0.5%
asn-2441538
 
0.4%
asn-2387526
 
0.3%
asn-3213819
 
0.2%
asn-2803617
 
0.2%
asn-2803417
 
0.2%
dn-30417
 
0.2%
asn-2803317
 
0.2%
asn-3079217
 
0.2%
asn-152016
 
0.2%
Other values (7020)10086
97.7%

Most occurring characters

ValueCountFrequency (%)
N10324
13.1%
-10324
13.1%
26558
 
8.3%
16137
 
7.8%
35629
 
7.1%
D5404
 
6.9%
A4920
 
6.2%
S4920
 
6.2%
43911
 
5.0%
73586
 
4.6%
Other values (5)17030
21.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number42851
54.4%
Uppercase Letter25568
32.5%
Dash Punctuation10324
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
26558
15.3%
16137
14.3%
35629
13.1%
43911
9.1%
73586
8.4%
53562
8.3%
63422
8.0%
83372
7.9%
93351
7.8%
03323
7.8%
Uppercase Letter
ValueCountFrequency (%)
N10324
40.4%
D5404
21.1%
A4920
19.2%
S4920
19.2%
Dash Punctuation
ValueCountFrequency (%)
-10324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common53175
67.5%
Latin25568
32.5%

Most frequent character per script

Common
ValueCountFrequency (%)
-10324
19.4%
26558
12.3%
16137
11.5%
35629
10.6%
43911
 
7.4%
73586
 
6.7%
53562
 
6.7%
63422
 
6.4%
83372
 
6.3%
93351
 
6.3%
Latin
ValueCountFrequency (%)
N10324
40.4%
D5404
21.1%
A4920
19.2%
S4920
19.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII78743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N10324
13.1%
-10324
13.1%
26558
 
8.3%
16137
 
7.8%
35629
 
7.1%
D5404
 
6.9%
A4920
 
6.2%
S4920
 
6.2%
43911
 
5.0%
73586
 
4.6%
Other values (5)17030
21.6%

country
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
South Africa
1406 
Nigeria
1194 
Côte d'Ivoire
1083 
Uganda
779 
Vietnam
688 
Other values (38)
5174 

Length

Max length18
Median length12
Mean length8.476268888
Min length4

Characters and Unicode

Total characters87509
Distinct characters48
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowCôte d'Ivoire
2nd rowVietnam
3rd rowCôte d'Ivoire
4th rowVietnam
5th rowVietnam

Common Values

ValueCountFrequency (%)
South Africa1406
13.6%
Nigeria1194
11.6%
Côte d'Ivoire1083
10.5%
Uganda779
 
7.5%
Vietnam688
 
6.7%
Zambia683
 
6.6%
Haiti655
 
6.3%
Mozambique631
 
6.1%
Zimbabwe538
 
5.2%
Tanzania519
 
5.0%
Other values (33)2148
20.8%

Length

2022-09-29T11:28:05.406851image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
south1570
11.7%
africa1406
 
10.5%
nigeria1194
 
8.9%
côte1083
 
8.1%
d'ivoire1083
 
8.1%
uganda779
 
5.8%
vietnam688
 
5.1%
zambia683
 
5.1%
haiti655
 
4.9%
mozambique631
 
4.7%
Other values (38)3596
26.9%

Most occurring characters

ValueCountFrequency (%)
a12282
 
14.0%
i10247
 
11.7%
e5522
 
6.3%
o4473
 
5.1%
n4350
 
5.0%
t4323
 
4.9%
r3874
 
4.4%
3044
 
3.5%
u2914
 
3.3%
m2777
 
3.2%
Other values (38)33703
38.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter69015
78.9%
Uppercase Letter14034
 
16.0%
Space Separator3044
 
3.5%
Other Punctuation1416
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a12282
17.8%
i10247
14.8%
e5522
 
8.0%
o4473
 
6.5%
n4350
 
6.3%
t4323
 
6.3%
r3874
 
5.6%
u2914
 
4.2%
m2777
 
4.0%
d2635
 
3.8%
Other values (15)15618
22.6%
Uppercase Letter
ValueCountFrequency (%)
C1824
13.0%
S1822
13.0%
A1416
10.1%
N1289
9.2%
Z1221
8.7%
I1083
7.7%
R815
 
5.8%
U779
 
5.6%
V688
 
4.9%
M662
 
4.7%
Other values (10)2435
17.4%
Other Punctuation
ValueCountFrequency (%)
'1083
76.5%
,333
 
23.5%
Space Separator
ValueCountFrequency (%)
3044
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin83049
94.9%
Common4460
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a12282
14.8%
i10247
 
12.3%
e5522
 
6.6%
o4473
 
5.4%
n4350
 
5.2%
t4323
 
5.2%
r3874
 
4.7%
u2914
 
3.5%
m2777
 
3.3%
d2635
 
3.2%
Other values (35)29652
35.7%
Common
ValueCountFrequency (%)
3044
68.3%
'1083
 
24.3%
,333
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII86426
98.8%
Latin 1 Sup1083
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a12282
 
14.2%
i10247
 
11.9%
e5522
 
6.4%
o4473
 
5.2%
n4350
 
5.0%
t4323
 
5.0%
r3874
 
4.5%
3044
 
3.5%
u2914
 
3.4%
m2777
 
3.2%
Other values (37)32620
37.7%
Latin 1 Sup
ValueCountFrequency (%)
ô1083
100.0%

managed by
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
PMO - US
10265 
South Africa Field Office
 
57
Haiti Field Office
 
1
Ethiopia Field Office
 
1

Length

Max length25
Median length8
Mean length8.096086788
Min length8

Characters and Unicode

Total characters83584
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowPMO - US
2nd rowPMO - US
3rd rowPMO - US
4th rowPMO - US
5th rowPMO - US

Common Values

ValueCountFrequency (%)
PMO - US10265
99.4%
South Africa Field Office57
 
0.6%
Haiti Field Office1
 
< 0.1%
Ethiopia Field Office1
 
< 0.1%

Length

2022-09-29T11:28:05.522539image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-29T11:28:05.645555image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
pmo10265
33.1%
10265
33.1%
us10265
33.1%
field59
 
0.2%
office59
 
0.2%
south57
 
0.2%
africa57
 
0.2%
haiti1
 
< 0.1%
ethiopia1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
20705
24.8%
O10324
12.4%
S10322
12.3%
P10265
12.3%
M10265
12.3%
-10265
12.3%
U10265
12.3%
i179
 
0.2%
f175
 
0.2%
e118
 
0.1%
Other values (14)701
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter51559
61.7%
Space Separator20705
24.8%
Dash Punctuation10265
 
12.3%
Lowercase Letter1055
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i179
17.0%
f175
16.6%
e118
11.2%
c116
11.0%
t59
 
5.6%
a59
 
5.6%
l59
 
5.6%
d59
 
5.6%
h58
 
5.5%
o58
 
5.5%
Other values (3)115
10.9%
Uppercase Letter
ValueCountFrequency (%)
O10324
20.0%
S10322
20.0%
P10265
19.9%
M10265
19.9%
U10265
19.9%
F59
 
0.1%
A57
 
0.1%
H1
 
< 0.1%
E1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
20705
100.0%
Dash Punctuation
ValueCountFrequency (%)
-10265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin52614
62.9%
Common30970
37.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O10324
19.6%
S10322
19.6%
P10265
19.5%
M10265
19.5%
U10265
19.5%
i179
 
0.3%
f175
 
0.3%
e118
 
0.2%
c116
 
0.2%
t59
 
0.1%
Other values (12)526
 
1.0%
Common
ValueCountFrequency (%)
20705
66.9%
-10265
33.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII83584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20705
24.8%
O10324
12.4%
S10322
12.3%
P10265
12.3%
M10265
12.3%
-10265
12.3%
U10265
12.3%
i179
 
0.2%
f175
 
0.2%
e118
 
0.1%
Other values (14)701
 
0.8%

fulfill via
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
From RDC
5404 
Direct Drop
4920 

Length

Max length11
Median length8
Mean length9.429678419
Min length8

Characters and Unicode

Total characters97352
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDirect Drop
2nd rowDirect Drop
3rd rowDirect Drop
4th rowDirect Drop
5th rowDirect Drop

Common Values

ValueCountFrequency (%)
From RDC5404
52.3%
Direct Drop4920
47.7%

Length

2022-09-29T11:28:05.741816image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-29T11:28:05.838593image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
from5404
26.2%
rdc5404
26.2%
direct4920
23.8%
drop4920
23.8%

Most occurring characters

ValueCountFrequency (%)
r15244
15.7%
D15244
15.7%
o10324
10.6%
10324
10.6%
F5404
 
5.6%
m5404
 
5.6%
R5404
 
5.6%
C5404
 
5.6%
i4920
 
5.1%
e4920
 
5.1%
Other values (3)14760
15.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter55572
57.1%
Uppercase Letter31456
32.3%
Space Separator10324
 
10.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r15244
27.4%
o10324
18.6%
m5404
 
9.7%
i4920
 
8.9%
e4920
 
8.9%
c4920
 
8.9%
t4920
 
8.9%
p4920
 
8.9%
Uppercase Letter
ValueCountFrequency (%)
D15244
48.5%
F5404
 
17.2%
R5404
 
17.2%
C5404
 
17.2%
Space Separator
ValueCountFrequency (%)
10324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin87028
89.4%
Common10324
 
10.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r15244
17.5%
D15244
17.5%
o10324
11.9%
F5404
 
6.2%
m5404
 
6.2%
R5404
 
6.2%
C5404
 
6.2%
i4920
 
5.7%
e4920
 
5.7%
c4920
 
5.7%
Other values (2)9840
11.3%
Common
ValueCountFrequency (%)
10324
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII97352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r15244
15.7%
D15244
15.7%
o10324
10.6%
10324
10.6%
F5404
 
5.6%
m5404
 
5.6%
R5404
 
5.6%
C5404
 
5.6%
i4920
 
5.1%
e4920
 
5.1%
Other values (3)14760
15.2%

vendor inco term
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
N/A - From RDC
5404 
EXW
2778 
DDP
1443 
FCA
 
397
CIP
 
275
Other values (3)
 
27

Length

Max length14
Median length14
Mean length8.757845796
Min length3

Characters and Unicode

Total characters90416
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEXW
2nd rowEXW
3rd rowFCA
4th rowEXW
5th rowEXW

Common Values

ValueCountFrequency (%)
N/A - From RDC5404
52.3%
EXW2778
26.9%
DDP1443
 
14.0%
FCA397
 
3.8%
CIP275
 
2.7%
DDU15
 
0.1%
DAP9
 
0.1%
CIF3
 
< 0.1%

Length

2022-09-29T11:28:05.924937image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-29T11:28:06.040595image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
n/a5404
20.4%
5404
20.4%
from5404
20.4%
rdc5404
20.4%
exw2778
10.5%
ddp1443
 
5.4%
fca397
 
1.5%
cip275
 
1.0%
ddu15
 
0.1%
dap9
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
16212
17.9%
D8329
 
9.2%
C6079
 
6.7%
A5810
 
6.4%
F5804
 
6.4%
N5404
 
6.0%
m5404
 
6.0%
/5404
 
6.0%
R5404
 
6.0%
o5404
 
6.0%
Other values (8)21162
23.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter47184
52.2%
Space Separator16212
 
17.9%
Lowercase Letter16212
 
17.9%
Other Punctuation5404
 
6.0%
Dash Punctuation5404
 
6.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D8329
17.7%
C6079
12.9%
A5810
12.3%
F5804
12.3%
N5404
11.5%
R5404
11.5%
E2778
 
5.9%
X2778
 
5.9%
W2778
 
5.9%
P1727
 
3.7%
Other values (2)293
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
m5404
33.3%
o5404
33.3%
r5404
33.3%
Space Separator
ValueCountFrequency (%)
16212
100.0%
Other Punctuation
ValueCountFrequency (%)
/5404
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5404
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin63396
70.1%
Common27020
29.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
D8329
13.1%
C6079
9.6%
A5810
9.2%
F5804
9.2%
N5404
8.5%
m5404
8.5%
R5404
8.5%
o5404
8.5%
r5404
8.5%
E2778
 
4.4%
Other values (5)7576
12.0%
Common
ValueCountFrequency (%)
16212
60.0%
/5404
 
20.0%
-5404
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII90416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16212
17.9%
D8329
 
9.2%
C6079
 
6.7%
A5810
 
6.4%
F5804
 
6.4%
N5404
 
6.0%
m5404
 
6.0%
/5404
 
6.0%
R5404
 
6.0%
o5404
 
6.0%
Other values (8)21162
23.4%

shipment mode
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)< 0.1%
Missing360
Missing (%)3.5%
Memory size80.8 KiB
Air
6113 
Truck
2830 
Air Charter
650 
Ocean
 
371

Length

Max length11
Median length3
Mean length4.164391811
Min length3

Characters and Unicode

Total characters41494
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAir
2nd rowAir
3rd rowAir
4th rowAir
5th rowAir

Common Values

ValueCountFrequency (%)
Air6113
59.2%
Truck2830
27.4%
Air Charter650
 
6.3%
Ocean371
 
3.6%
(Missing)360
 
3.5%

Length

2022-09-29T11:28:06.169247image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-29T11:28:06.272015image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
air6763
63.7%
truck2830
26.7%
charter650
 
6.1%
ocean371
 
3.5%

Most occurring characters

ValueCountFrequency (%)
r10893
26.3%
A6763
16.3%
i6763
16.3%
c3201
 
7.7%
T2830
 
6.8%
u2830
 
6.8%
k2830
 
6.8%
a1021
 
2.5%
e1021
 
2.5%
650
 
1.6%
Other values (5)2692
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter30230
72.9%
Uppercase Letter10614
 
25.6%
Space Separator650
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r10893
36.0%
i6763
22.4%
c3201
 
10.6%
u2830
 
9.4%
k2830
 
9.4%
a1021
 
3.4%
e1021
 
3.4%
h650
 
2.2%
t650
 
2.2%
n371
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
A6763
63.7%
T2830
26.7%
C650
 
6.1%
O371
 
3.5%
Space Separator
ValueCountFrequency (%)
650
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin40844
98.4%
Common650
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r10893
26.7%
A6763
16.6%
i6763
16.6%
c3201
 
7.8%
T2830
 
6.9%
u2830
 
6.9%
k2830
 
6.9%
a1021
 
2.5%
e1021
 
2.5%
C650
 
1.6%
Other values (4)2042
 
5.0%
Common
ValueCountFrequency (%)
650
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII41494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r10893
26.3%
A6763
16.3%
i6763
16.3%
c3201
 
7.7%
T2830
 
6.8%
u2830
 
6.8%
k2830
 
6.8%
a1021
 
2.5%
e1021
 
2.5%
650
 
1.6%
Other values (5)2692
 
6.5%

pq first sent to client date
Categorical

HIGH CARDINALITY

Distinct765
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Pre-PQ Process
2476 
9/11/2014
 
205
Date Not Captured
 
205
7/11/2013
 
173
4/30/2014
 
123
Other values (760)
7142 

Length

Max length17
Median length14
Mean length10.35557923
Min length8

Characters and Unicode

Total characters106911
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)1.3%

Sample

1st rowPre-PQ Process
2nd rowPre-PQ Process
3rd rowPre-PQ Process
4th rowPre-PQ Process
5th rowPre-PQ Process

Common Values

ValueCountFrequency (%)
Pre-PQ Process2476
 
24.0%
9/11/2014205
 
2.0%
Date Not Captured205
 
2.0%
7/11/2013173
 
1.7%
4/30/2014123
 
1.2%
11/6/200998
 
0.9%
11/21/201190
 
0.9%
3/10/201189
 
0.9%
3/18/201078
 
0.8%
8/31/201075
 
0.7%
Other values (755)6712
65.0%

Length

2022-09-29T11:28:06.359739image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pre-pq2476
 
18.7%
process2476
 
18.7%
9/11/2014205
 
1.6%
date205
 
1.6%
not205
 
1.6%
captured205
 
1.6%
7/11/2013173
 
1.3%
4/30/2014123
 
0.9%
11/6/200998
 
0.7%
11/21/201190
 
0.7%
Other values (758)6954
52.6%

Most occurring characters

ValueCountFrequency (%)
115328
14.3%
/15286
14.3%
212611
11.8%
011326
10.6%
P7428
 
6.9%
e5362
 
5.0%
r5157
 
4.8%
s4952
 
4.6%
33479
 
3.3%
42986
 
2.8%
Other values (18)22996
21.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number53476
50.0%
Lowercase Letter22268
20.8%
Other Punctuation15286
 
14.3%
Uppercase Letter10519
 
9.8%
Space Separator2886
 
2.7%
Dash Punctuation2476
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
115328
28.7%
212611
23.6%
011326
21.2%
33479
 
6.5%
42986
 
5.6%
92280
 
4.3%
51516
 
2.8%
81508
 
2.8%
71283
 
2.4%
61159
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
e5362
24.1%
r5157
23.2%
s4952
22.2%
o2681
12.0%
c2476
11.1%
t615
 
2.8%
a410
 
1.8%
p205
 
0.9%
u205
 
0.9%
d205
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P7428
70.6%
Q2476
 
23.5%
N205
 
1.9%
D205
 
1.9%
C205
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/15286
100.0%
Space Separator
ValueCountFrequency (%)
2886
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2476
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common74124
69.3%
Latin32787
30.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
P7428
22.7%
e5362
16.4%
r5157
15.7%
s4952
15.1%
o2681
 
8.2%
c2476
 
7.6%
Q2476
 
7.6%
t615
 
1.9%
a410
 
1.3%
N205
 
0.6%
Other values (5)1025
 
3.1%
Common
ValueCountFrequency (%)
115328
20.7%
/15286
20.6%
212611
17.0%
011326
15.3%
33479
 
4.7%
42986
 
4.0%
2886
 
3.9%
-2476
 
3.3%
92280
 
3.1%
51516
 
2.0%
Other values (3)3950
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII106911
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
115328
14.3%
/15286
14.3%
212611
11.8%
011326
10.6%
P7428
 
6.9%
e5362
 
5.0%
r5157
 
4.8%
s4952
 
4.6%
33479
 
3.3%
42986
 
2.8%
Other values (18)22996
21.5%

po sent to vendor date
Categorical

HIGH CARDINALITY

Distinct897
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
N/A - From RDC
5404 
Date Not Captured
 
328
8/27/2014
 
80
3/19/2010
 
78
8/29/2014
 
76
Other values (892)
4358 

Length

Max length17
Median length14
Mean length11.84996126
Min length8

Characters and Unicode

Total characters122339
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)2.5%

Sample

1st rowDate Not Captured
2nd rowDate Not Captured
3rd rowDate Not Captured
4th rowDate Not Captured
5th rowDate Not Captured

Common Values

ValueCountFrequency (%)
N/A - From RDC5404
52.3%
Date Not Captured328
 
3.2%
8/27/201480
 
0.8%
3/19/201078
 
0.8%
8/29/201476
 
0.7%
10/9/201471
 
0.7%
12/2/201367
 
0.6%
9/24/201053
 
0.5%
2/20/201543
 
0.4%
5/11/201540
 
0.4%
Other values (887)4084
39.6%

Length

2022-09-29T11:28:06.452528image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
n/a5404
19.9%
5404
19.9%
from5404
19.9%
rdc5404
19.9%
date328
 
1.2%
not328
 
1.2%
captured328
 
1.2%
8/27/201480
 
0.3%
3/19/201078
 
0.3%
8/29/201476
 
0.3%
Other values (892)4358
16.0%

Most occurring characters

ValueCountFrequency (%)
16868
13.8%
/14588
 
11.9%
27921
 
6.5%
17602
 
6.2%
07063
 
5.8%
o5732
 
4.7%
D5732
 
4.7%
N5732
 
4.7%
r5732
 
4.7%
C5732
 
4.7%
Other values (18)39637
32.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter33408
27.3%
Decimal Number31923
26.1%
Lowercase Letter20148
16.5%
Space Separator16868
13.8%
Other Punctuation14588
11.9%
Dash Punctuation5404
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
27921
24.8%
17602
23.8%
07063
22.1%
31863
 
5.8%
41840
 
5.8%
91471
 
4.6%
81339
 
4.2%
51181
 
3.7%
7972
 
3.0%
6671
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
o5732
28.4%
r5732
28.4%
m5404
26.8%
t984
 
4.9%
a656
 
3.3%
e656
 
3.3%
d328
 
1.6%
u328
 
1.6%
p328
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
D5732
17.2%
N5732
17.2%
C5732
17.2%
R5404
16.2%
F5404
16.2%
A5404
16.2%
Space Separator
ValueCountFrequency (%)
16868
100.0%
Other Punctuation
ValueCountFrequency (%)
/14588
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5404
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common68783
56.2%
Latin53556
43.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o5732
10.7%
D5732
10.7%
N5732
10.7%
r5732
10.7%
C5732
10.7%
m5404
10.1%
R5404
10.1%
F5404
10.1%
A5404
10.1%
t984
 
1.8%
Other values (5)2296
4.3%
Common
ValueCountFrequency (%)
16868
24.5%
/14588
21.2%
27921
11.5%
17602
11.1%
07063
10.3%
-5404
 
7.9%
31863
 
2.7%
41840
 
2.7%
91471
 
2.1%
81339
 
1.9%
Other values (3)2824
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII122339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16868
13.8%
/14588
 
11.9%
27921
 
6.5%
17602
 
6.2%
07063
 
5.8%
o5732
 
4.7%
D5732
 
4.7%
N5732
 
4.7%
r5732
 
4.7%
C5732
 
4.7%
Other values (18)39637
32.4%

scheduled delivery date
Categorical

HIGH CARDINALITY

Distinct2006
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
29-Aug-14
 
97
16-Mar-12
 
83
27-Aug-14
 
63
31-May-10
 
62
31-Jan-14
 
60
Other values (2001)
9959 

Length

Max length9
Median length9
Mean length8.754455637
Min length8

Characters and Unicode

Total characters90381
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique492 ?
Unique (%)4.8%

Sample

1st row2-Jun-06
2nd row14-Nov-06
3rd row27-Aug-06
4th row1-Sep-06
5th row11-Aug-06

Common Values

ValueCountFrequency (%)
29-Aug-1497
 
0.9%
16-Mar-1283
 
0.8%
27-Aug-1463
 
0.6%
31-May-1062
 
0.6%
31-Jan-1460
 
0.6%
30-Sep-1457
 
0.6%
16-Apr-1356
 
0.5%
15-Jul-1055
 
0.5%
19-Apr-1053
 
0.5%
24-Aug-1551
 
0.5%
Other values (1996)9687
93.8%

Length

2022-09-29T11:28:06.567221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
29-aug-1497
 
0.9%
16-mar-1283
 
0.8%
27-aug-1463
 
0.6%
31-may-1062
 
0.6%
31-jan-1460
 
0.6%
30-sep-1457
 
0.6%
16-apr-1356
 
0.5%
15-jul-1055
 
0.5%
19-apr-1053
 
0.5%
24-aug-1551
 
0.5%
Other values (1996)9687
93.8%

Most occurring characters

ValueCountFrequency (%)
-20648
22.8%
112920
14.3%
05704
 
6.3%
25279
 
5.8%
33605
 
4.0%
u2949
 
3.3%
J2584
 
2.9%
a2522
 
2.8%
42483
 
2.7%
92351
 
2.6%
Other values (23)29336
32.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number38761
42.9%
Dash Punctuation20648
22.8%
Lowercase Letter20648
22.8%
Uppercase Letter10324
 
11.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u2949
14.3%
a2522
12.2%
e2283
11.1%
r1964
9.5%
p1847
8.9%
n1667
8.1%
c1502
7.3%
g1081
 
5.2%
l917
 
4.4%
t822
 
4.0%
Other values (4)3094
15.0%
Decimal Number
ValueCountFrequency (%)
112920
33.3%
05704
14.7%
25279
13.6%
33605
 
9.3%
42483
 
6.4%
92351
 
6.1%
51970
 
5.1%
81918
 
4.9%
71572
 
4.1%
6959
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
J2584
25.0%
A2044
19.8%
M1806
17.5%
S884
 
8.6%
O822
 
8.0%
N785
 
7.6%
F719
 
7.0%
D680
 
6.6%
Dash Punctuation
ValueCountFrequency (%)
-20648
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common59409
65.7%
Latin30972
34.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
u2949
 
9.5%
J2584
 
8.3%
a2522
 
8.1%
e2283
 
7.4%
A2044
 
6.6%
r1964
 
6.3%
p1847
 
6.0%
M1806
 
5.8%
n1667
 
5.4%
c1502
 
4.8%
Other values (12)9804
31.7%
Common
ValueCountFrequency (%)
-20648
34.8%
112920
21.7%
05704
 
9.6%
25279
 
8.9%
33605
 
6.1%
42483
 
4.2%
92351
 
4.0%
51970
 
3.3%
81918
 
3.2%
71572
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII90381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-20648
22.8%
112920
14.3%
05704
 
6.3%
25279
 
5.8%
33605
 
4.0%
u2949
 
3.3%
J2584
 
2.9%
a2522
 
2.8%
42483
 
2.7%
92351
 
2.6%
Other values (23)29336
32.5%

delivered to client date
Categorical

HIGH CARDINALITY

Distinct2093
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
29-Aug-14
 
74
27-Aug-14
 
66
28-Jun-10
 
60
14-Feb-12
 
60
16-Apr-13
 
59
Other values (2088)
10005 

Length

Max length9
Median length9
Mean length8.717938783
Min length8

Characters and Unicode

Total characters90004
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)4.6%

Sample

1st row2-Jun-06
2nd row14-Nov-06
3rd row27-Aug-06
4th row1-Sep-06
5th row11-Aug-06

Common Values

ValueCountFrequency (%)
29-Aug-1474
 
0.7%
27-Aug-1466
 
0.6%
28-Jun-1060
 
0.6%
14-Feb-1260
 
0.6%
16-Apr-1359
 
0.6%
31-Mar-1052
 
0.5%
24-Aug-1551
 
0.5%
12-May-1541
 
0.4%
18-May-1041
 
0.4%
6-Feb-1439
 
0.4%
Other values (2083)9781
94.7%

Length

2022-09-29T11:28:06.681910image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
29-aug-1474
 
0.7%
27-aug-1466
 
0.6%
28-jun-1060
 
0.6%
14-feb-1260
 
0.6%
16-apr-1359
 
0.6%
31-mar-1052
 
0.5%
24-aug-1551
 
0.5%
18-may-1041
 
0.4%
12-may-1541
 
0.4%
6-feb-1439
 
0.4%
Other values (2083)9781
94.7%

Most occurring characters

ValueCountFrequency (%)
-20648
22.9%
112777
14.2%
25679
 
6.3%
05284
 
5.9%
u2829
 
3.1%
42823
 
3.1%
32810
 
3.1%
a2518
 
2.8%
J2490
 
2.8%
e2420
 
2.7%
Other values (23)29726
33.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number38384
42.6%
Dash Punctuation20648
22.9%
Lowercase Letter20648
22.9%
Uppercase Letter10324
 
11.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u2829
13.7%
a2518
12.2%
e2420
11.7%
r1863
9.0%
p1751
8.5%
n1618
7.8%
c1562
7.6%
g1030
 
5.0%
l872
 
4.2%
t867
 
4.2%
Other values (4)3318
16.1%
Decimal Number
ValueCountFrequency (%)
112777
33.3%
25679
14.8%
05284
13.8%
42823
 
7.4%
32810
 
7.3%
92268
 
5.9%
82192
 
5.7%
51959
 
5.1%
71673
 
4.4%
6919
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
J2490
24.1%
A1921
18.6%
M1827
17.7%
O867
 
8.4%
F865
 
8.4%
S860
 
8.3%
N799
 
7.7%
D695
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
-20648
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common59032
65.6%
Latin30972
34.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
u2829
 
9.1%
a2518
 
8.1%
J2490
 
8.0%
e2420
 
7.8%
A1921
 
6.2%
r1863
 
6.0%
M1827
 
5.9%
p1751
 
5.7%
n1618
 
5.2%
c1562
 
5.0%
Other values (12)10173
32.8%
Common
ValueCountFrequency (%)
-20648
35.0%
112777
21.6%
25679
 
9.6%
05284
 
9.0%
42823
 
4.8%
32810
 
4.8%
92268
 
3.8%
82192
 
3.7%
51959
 
3.3%
71673
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII90004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-20648
22.9%
112777
14.2%
25679
 
6.3%
05284
 
5.9%
u2829
 
3.1%
42823
 
3.1%
32810
 
3.1%
a2518
 
2.8%
J2490
 
2.8%
e2420
 
2.7%
Other values (23)29726
33.0%

delivery recorded date
Categorical

HIGH CARDINALITY

Distinct2042
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
29-Aug-14
 
67
27-Aug-14
 
66
14-Feb-12
 
60
28-Jun-10
 
60
16-Apr-13
 
59
Other values (2037)
10012 

Length

Max length9
Median length9
Mean length8.719004262
Min length8

Characters and Unicode

Total characters90015
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique468 ?
Unique (%)4.5%

Sample

1st row2-Jun-06
2nd row14-Nov-06
3rd row27-Aug-06
4th row1-Sep-06
5th row11-Aug-06

Common Values

ValueCountFrequency (%)
29-Aug-1467
 
0.6%
27-Aug-1466
 
0.6%
14-Feb-1260
 
0.6%
28-Jun-1060
 
0.6%
16-Apr-1359
 
0.6%
31-Mar-1052
 
0.5%
24-Aug-1550
 
0.5%
18-May-1041
 
0.4%
12-May-1540
 
0.4%
7-Nov-1439
 
0.4%
Other values (2032)9790
94.8%

Length

2022-09-29T11:28:06.788624image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
29-aug-1467
 
0.6%
27-aug-1466
 
0.6%
14-feb-1260
 
0.6%
28-jun-1060
 
0.6%
16-apr-1359
 
0.6%
31-mar-1052
 
0.5%
24-aug-1550
 
0.5%
18-may-1041
 
0.4%
12-may-1540
 
0.4%
7-nov-1439
 
0.4%
Other values (2032)9790
94.8%

Most occurring characters

ValueCountFrequency (%)
-20648
22.9%
112905
14.3%
25632
 
6.3%
05247
 
5.8%
u2877
 
3.2%
42813
 
3.1%
32757
 
3.1%
a2533
 
2.8%
J2520
 
2.8%
e2375
 
2.6%
Other values (23)29708
33.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number38395
42.7%
Dash Punctuation20648
22.9%
Lowercase Letter20648
22.9%
Uppercase Letter10324
 
11.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u2877
13.9%
a2533
12.3%
e2375
11.5%
r1891
9.2%
p1720
8.3%
n1649
8.0%
c1502
7.3%
g1045
 
5.1%
o880
 
4.3%
v880
 
4.3%
Other values (4)3296
16.0%
Decimal Number
ValueCountFrequency (%)
112905
33.6%
25632
14.7%
05247
13.7%
42813
 
7.3%
32757
 
7.2%
92240
 
5.8%
82155
 
5.6%
51918
 
5.0%
71745
 
4.5%
6983
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
J2520
24.4%
A1912
18.5%
M1845
17.9%
N880
 
8.5%
S853
 
8.3%
F812
 
7.9%
O792
 
7.7%
D710
 
6.9%
Dash Punctuation
ValueCountFrequency (%)
-20648
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common59043
65.6%
Latin30972
34.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
u2877
 
9.3%
a2533
 
8.2%
J2520
 
8.1%
e2375
 
7.7%
A1912
 
6.2%
r1891
 
6.1%
M1845
 
6.0%
p1720
 
5.6%
n1649
 
5.3%
c1502
 
4.8%
Other values (12)10148
32.8%
Common
ValueCountFrequency (%)
-20648
35.0%
112905
21.9%
25632
 
9.5%
05247
 
8.9%
42813
 
4.8%
32757
 
4.7%
92240
 
3.8%
82155
 
3.6%
51918
 
3.2%
71745
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII90015
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-20648
22.9%
112905
14.3%
25632
 
6.3%
05247
 
5.8%
u2877
 
3.2%
42813
 
3.1%
32757
 
3.1%
a2533
 
2.8%
J2520
 
2.8%
e2375
 
2.6%
Other values (23)29708
33.0%

product group
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
ARV
8550 
HRDT
1728 
ANTM
 
22
ACT
 
16
MRDT
 
8

Length

Max length4
Median length3
Mean length3.170282836
Min length3

Characters and Unicode

Total characters32730
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHRDT
2nd rowARV
3rd rowHRDT
4th rowARV
5th rowARV

Common Values

ValueCountFrequency (%)
ARV8550
82.8%
HRDT1728
 
16.7%
ANTM22
 
0.2%
ACT16
 
0.2%
MRDT8
 
0.1%

Length

2022-09-29T11:28:06.890319image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-29T11:28:07.001056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
arv8550
82.8%
hrdt1728
 
16.7%
antm22
 
0.2%
act16
 
0.2%
mrdt8
 
0.1%

Most occurring characters

ValueCountFrequency (%)
R10286
31.4%
A8588
26.2%
V8550
26.1%
T1774
 
5.4%
D1736
 
5.3%
H1728
 
5.3%
M30
 
0.1%
N22
 
0.1%
C16
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter32730
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R10286
31.4%
A8588
26.2%
V8550
26.1%
T1774
 
5.4%
D1736
 
5.3%
H1728
 
5.3%
M30
 
0.1%
N22
 
0.1%
C16
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin32730
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R10286
31.4%
A8588
26.2%
V8550
26.1%
T1774
 
5.4%
D1736
 
5.3%
H1728
 
5.3%
M30
 
0.1%
N22
 
0.1%
C16
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R10286
31.4%
A8588
26.2%
V8550
26.1%
T1774
 
5.4%
D1736
 
5.3%
H1728
 
5.3%
M30
 
0.1%
N22
 
0.1%
C16
 
< 0.1%

sub classification
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Adult
6595 
Pediatric
1955 
HIV test
1567 
HIV test - Ancillary
 
161
Malaria
 
30

Length

Max length20
Median length5
Mean length6.449438202
Min length3

Characters and Unicode

Total characters66584
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHIV test
2nd rowPediatric
3rd rowHIV test
4th rowAdult
5th rowAdult

Common Values

ValueCountFrequency (%)
Adult6595
63.9%
Pediatric1955
 
18.9%
HIV test1567
 
15.2%
HIV test - Ancillary161
 
1.6%
Malaria30
 
0.3%
ACT16
 
0.2%

Length

2022-09-29T11:28:07.099791image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-29T11:28:07.212457image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
adult6595
53.3%
pediatric1955
 
15.8%
hiv1728
 
14.0%
test1728
 
14.0%
161
 
1.3%
ancillary161
 
1.3%
malaria30
 
0.2%
act16
 
0.1%

Most occurring characters

ValueCountFrequency (%)
t12006
18.0%
d8550
12.8%
l6947
10.4%
A6772
10.2%
u6595
9.9%
i4101
 
6.2%
e3683
 
5.5%
a2206
 
3.3%
r2146
 
3.2%
c2116
 
3.2%
Other values (12)11462
17.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter50400
75.7%
Uppercase Letter13973
 
21.0%
Space Separator2050
 
3.1%
Dash Punctuation161
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t12006
23.8%
d8550
17.0%
l6947
13.8%
u6595
13.1%
i4101
 
8.1%
e3683
 
7.3%
a2206
 
4.4%
r2146
 
4.3%
c2116
 
4.2%
s1728
 
3.4%
Other values (2)322
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
A6772
48.5%
P1955
 
14.0%
H1728
 
12.4%
V1728
 
12.4%
I1728
 
12.4%
M30
 
0.2%
C16
 
0.1%
T16
 
0.1%
Space Separator
ValueCountFrequency (%)
2050
100.0%
Dash Punctuation
ValueCountFrequency (%)
-161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin64373
96.7%
Common2211
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t12006
18.7%
d8550
13.3%
l6947
10.8%
A6772
10.5%
u6595
10.2%
i4101
 
6.4%
e3683
 
5.7%
a2206
 
3.4%
r2146
 
3.3%
c2116
 
3.3%
Other values (10)9251
14.4%
Common
ValueCountFrequency (%)
2050
92.7%
-161
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII66584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t12006
18.0%
d8550
12.8%
l6947
10.4%
A6772
10.2%
u6595
9.9%
i4101
 
6.2%
e3683
 
5.5%
a2206
 
3.3%
r2146
 
3.2%
c2116
 
3.2%
Other values (12)11462
17.2%

vendor
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct73
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
SCMS from RDC
5404 
Orgenics, Ltd
754 
S. BUYS WHOLESALER
715 
Aurobindo Pharma Limited
668 
Trinity Biotech, Plc
 
356
Other values (68)
2427 

Length

Max length65
Median length13
Mean length18.53332042
Min length7

Characters and Unicode

Total characters191338
Distinct characters54
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st rowRANBAXY Fine Chemicals LTD.
2nd rowAurobindo Pharma Limited
3rd rowAbbott GmbH & Co. KG
4th rowSUN PHARMACEUTICAL INDUSTRIES LTD (RANBAXY LABORATORIES LIMITED)
5th rowAurobindo Pharma Limited

Common Values

ValueCountFrequency (%)
SCMS from RDC5404
52.3%
Orgenics, Ltd754
 
7.3%
S. BUYS WHOLESALER715
 
6.9%
Aurobindo Pharma Limited668
 
6.5%
Trinity Biotech, Plc356
 
3.4%
ABBVIE LOGISTICS (FORMERLY ABBOTT LOGISTICS BV)347
 
3.4%
PHARMACY DIRECT326
 
3.2%
MYLAN LABORATORIES LTD (FORMERLY MATRIX LABORATORIES)317
 
3.1%
HETERO LABS LIMITED277
 
2.7%
CIPLA LIMITED175
 
1.7%
Other values (63)985
 
9.5%

Length

2022-09-29T11:28:07.355113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scms5404
16.5%
rdc5404
16.5%
from5404
16.5%
limited1288
 
3.9%
ltd1169
 
3.6%
orgenics754
 
2.3%
s717
 
2.2%
buys715
 
2.2%
wholesaler715
 
2.2%
laboratories705
 
2.2%
Other values (158)10470
32.0%

Most occurring characters

ValueCountFrequency (%)
22491
 
11.8%
S16965
 
8.9%
C13420
 
7.0%
R11481
 
6.0%
M8653
 
4.5%
r8112
 
4.2%
D7485
 
3.9%
o7434
 
3.9%
L7380
 
3.9%
m6798
 
3.6%
Other values (44)81119
42.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter113980
59.6%
Lowercase Letter49941
26.1%
Space Separator22491
 
11.8%
Other Punctuation3054
 
1.6%
Open Punctuation876
 
0.5%
Close Punctuation875
 
0.5%
Dash Punctuation120
 
0.1%
Decimal Number1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S16965
14.9%
C13420
11.8%
R11481
10.1%
M8653
 
7.6%
D7485
 
6.6%
L7380
 
6.5%
A6789
 
6.0%
I6343
 
5.6%
E6253
 
5.5%
O5958
 
5.2%
Other values (16)23253
20.4%
Lowercase Letter
ValueCountFrequency (%)
r8112
16.2%
o7434
14.9%
m6798
13.6%
f5450
10.9%
i4120
8.2%
t2421
 
4.8%
d2333
 
4.7%
n2244
 
4.5%
e2034
 
4.1%
c1811
 
3.6%
Other values (9)7184
14.4%
Other Punctuation
ValueCountFrequency (%)
,1438
47.1%
.1406
46.0%
&207
 
6.8%
/3
 
0.1%
Space Separator
ValueCountFrequency (%)
22491
100.0%
Open Punctuation
ValueCountFrequency (%)
(876
100.0%
Close Punctuation
ValueCountFrequency (%)
)875
100.0%
Dash Punctuation
ValueCountFrequency (%)
-120
100.0%
Decimal Number
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin163921
85.7%
Common27417
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S16965
 
10.3%
C13420
 
8.2%
R11481
 
7.0%
M8653
 
5.3%
r8112
 
4.9%
D7485
 
4.6%
o7434
 
4.5%
L7380
 
4.5%
m6798
 
4.1%
A6789
 
4.1%
Other values (35)69404
42.3%
Common
ValueCountFrequency (%)
22491
82.0%
,1438
 
5.2%
.1406
 
5.1%
(876
 
3.2%
)875
 
3.2%
&207
 
0.8%
-120
 
0.4%
/3
 
< 0.1%
11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII191338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22491
 
11.8%
S16965
 
8.9%
C13420
 
7.0%
R11481
 
6.0%
M8653
 
4.5%
r8112
 
4.2%
D7485
 
3.9%
o7434
 
3.9%
L7380
 
3.9%
m6798
 
3.6%
Other values (44)81119
42.4%

item description
Categorical

HIGH CARDINALITY

Distinct184
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Efavirenz 600mg, tablets, 30 Tabs
755 
Nevirapine 200mg, tablets, 60 Tabs
 
623
Lamivudine/Zidovudine 150/300mg, tablets, 60 Tabs
 
597
Lamivudine/Nevirapine/Zidovudine 150/200/300mg, tablets, 60 Tabs
 
580
HIV 1/2, Determine Complete HIV Kit, 100 Tests
 
577
Other values (179)
7192 

Length

Max length113
Median length79
Mean length50.14480821
Min length31

Characters and Unicode

Total characters517695
Distinct characters73
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.2%

Sample

1st rowHIV, Reveal G3 Rapid HIV-1 Antibody Test, 30 Tests
2nd rowNevirapine 10mg/ml, oral suspension, Bottle, 240 ml
3rd rowHIV 1/2, Determine Complete HIV Kit, 100 Tests
4th rowLamivudine 150mg, tablets, 60 Tabs
5th rowStavudine 30mg, capsules, 60 Caps

Common Values

ValueCountFrequency (%)
Efavirenz 600mg, tablets, 30 Tabs755
 
7.3%
Nevirapine 200mg, tablets, 60 Tabs623
 
6.0%
Lamivudine/Zidovudine 150/300mg, tablets, 60 Tabs597
 
5.8%
Lamivudine/Nevirapine/Zidovudine 150/200/300mg, tablets, 60 Tabs580
 
5.6%
HIV 1/2, Determine Complete HIV Kit, 100 Tests577
 
5.6%
Lamivudine 150mg, tablets, 60 Tabs378
 
3.7%
HIV 1/2, Uni-Gold HIV Kit, 20 Tests369
 
3.6%
Zidovudine 300mg, tablets, 60 Tabs317
 
3.1%
Lamivudine/Tenofovir Disoproxil Fumarate 300/300mg, tablets, 30 Tabs301
 
2.9%
Abacavir 300mg, tablets, 60 Tabs287
 
2.8%
Other values (174)5540
53.7%

Length

2022-09-29T11:28:07.485760image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tablets6733
 
10.3%
tabs6711
 
10.2%
604269
 
6.5%
hiv3006
 
4.6%
302598
 
4.0%
tests1616
 
2.5%
kit1579
 
2.4%
1/21524
 
2.3%
disoproxil1300
 
2.0%
fumarate1300
 
2.0%
Other values (289)34956
53.3%

Most occurring characters

ValueCountFrequency (%)
55268
 
10.7%
i33699
 
6.5%
a33528
 
6.5%
033249
 
6.4%
e33073
 
6.4%
t26685
 
5.2%
s24970
 
4.8%
,22576
 
4.4%
l17483
 
3.4%
n17399
 
3.4%
Other values (63)219765
42.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter313250
60.5%
Decimal Number65180
 
12.6%
Space Separator55268
 
10.7%
Uppercase Letter43918
 
8.5%
Other Punctuation36237
 
7.0%
Open Punctuation1507
 
0.3%
Close Punctuation1507
 
0.3%
Dash Punctuation764
 
0.1%
Math Symbol64
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i33699
10.8%
a33528
10.7%
e33073
10.6%
t26685
 
8.5%
s24970
 
8.0%
l17483
 
5.6%
n17399
 
5.6%
m17064
 
5.4%
o15781
 
5.0%
b15186
 
4.8%
Other values (16)78382
25.0%
Uppercase Letter
ValueCountFrequency (%)
T9901
22.5%
L4176
9.5%
V3366
 
7.7%
I3344
 
7.6%
H3086
 
7.0%
D2581
 
5.9%
E2144
 
4.9%
Z2052
 
4.7%
N2045
 
4.7%
C1971
 
4.5%
Other values (13)9252
21.1%
Decimal Number
ValueCountFrequency (%)
033249
51.0%
37689
 
11.8%
26712
 
10.3%
16430
 
9.9%
65928
 
9.1%
53521
 
5.4%
4991
 
1.5%
8366
 
0.6%
9241
 
0.4%
753
 
0.1%
Other Punctuation
ValueCountFrequency (%)
,22576
62.3%
/13314
36.7%
.220
 
0.6%
*84
 
0.2%
#42
 
0.1%
&1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[1445
95.9%
(62
 
4.1%
Close Punctuation
ValueCountFrequency (%)
]1445
95.9%
)62
 
4.1%
Math Symbol
ValueCountFrequency (%)
+62
96.9%
|2
 
3.1%
Space Separator
ValueCountFrequency (%)
55268
100.0%
Dash Punctuation
ValueCountFrequency (%)
-764
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin357168
69.0%
Common160527
31.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i33699
 
9.4%
a33528
 
9.4%
e33073
 
9.3%
t26685
 
7.5%
s24970
 
7.0%
l17483
 
4.9%
n17399
 
4.9%
m17064
 
4.8%
o15781
 
4.4%
b15186
 
4.3%
Other values (39)122300
34.2%
Common
ValueCountFrequency (%)
55268
34.4%
033249
20.7%
,22576
14.1%
/13314
 
8.3%
37689
 
4.8%
26712
 
4.2%
16430
 
4.0%
65928
 
3.7%
53521
 
2.2%
[1445
 
0.9%
Other values (14)4395
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII517695
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55268
 
10.7%
i33699
 
6.5%
a33528
 
6.5%
033249
 
6.4%
e33073
 
6.4%
t26685
 
5.2%
s24970
 
4.8%
,22576
 
4.4%
l17483
 
3.4%
n17399
 
3.4%
Other values (63)219765
42.5%

molecule/test type
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct86
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Efavirenz
1125 
Nevirapine
877 
Lamivudine/Nevirapine/Zidovudine
707 
Lamivudine/Zidovudine
689 
Lopinavir/Ritonavir
633 
Other values (81)
6293 

Length

Max length98
Median length60
Mean length22.1509105
Min length7

Characters and Unicode

Total characters228686
Distinct characters63
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.1%

Sample

1st rowHIV, Reveal G3 Rapid HIV-1 Antibody Test
2nd rowNevirapine
3rd rowHIV 1/2, Determine Complete HIV Kit
4th rowLamivudine
5th rowStavudine

Common Values

ValueCountFrequency (%)
Efavirenz1125
 
10.9%
Nevirapine877
 
8.5%
Lamivudine/Nevirapine/Zidovudine707
 
6.8%
Lamivudine/Zidovudine689
 
6.7%
Lopinavir/Ritonavir633
 
6.1%
Lamivudine592
 
5.7%
HIV 1/2, Determine Complete HIV Kit577
 
5.6%
Zidovudine529
 
5.1%
Abacavir453
 
4.4%
HIV 1/2, Uni-Gold HIV Kit369
 
3.6%
Other values (76)3773
36.5%

Length

2022-09-29T11:28:07.742292image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hiv3055
 
13.6%
kit1579
 
7.0%
1/21524
 
6.8%
disoproxil1300
 
5.8%
fumarate1300
 
5.8%
efavirenz1125
 
5.0%
nevirapine877
 
3.9%
determine799
 
3.6%
lamivudine/nevirapine/zidovudine707
 
3.2%
lamivudine/zidovudine689
 
3.1%
Other values (148)9451
42.2%

Most occurring characters

ValueCountFrequency (%)
i30297
 
13.2%
e19499
 
8.5%
a15535
 
6.8%
n15469
 
6.8%
v13084
 
5.7%
12082
 
5.3%
r11537
 
5.0%
o10997
 
4.8%
d9170
 
4.0%
t8291
 
3.6%
Other values (53)82725
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter169993
74.3%
Uppercase Letter32022
 
14.0%
Space Separator12082
 
5.3%
Other Punctuation9777
 
4.3%
Decimal Number4138
 
1.8%
Dash Punctuation572
 
0.3%
Open Punctuation39
 
< 0.1%
Close Punctuation39
 
< 0.1%
Math Symbol24
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i30297
17.8%
e19499
11.5%
a15535
9.1%
n15469
9.1%
v13084
7.7%
r11537
 
6.8%
o10997
 
6.5%
d9170
 
5.4%
t8291
 
4.9%
u7804
 
4.6%
Other values (15)28310
16.7%
Uppercase Letter
ValueCountFrequency (%)
L4176
13.0%
I3245
10.1%
V3176
9.9%
H3120
9.7%
D2573
 
8.0%
E2061
 
6.4%
Z1969
 
6.1%
N1901
 
5.9%
K1579
 
4.9%
T1515
 
4.7%
Other values (13)6707
20.9%
Decimal Number
ValueCountFrequency (%)
11786
43.2%
21644
39.7%
0478
 
11.6%
3148
 
3.6%
582
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/6734
68.9%
,2836
29.0%
.206
 
2.1%
&1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+22
91.7%
|2
 
8.3%
Space Separator
ValueCountFrequency (%)
12082
100.0%
Dash Punctuation
ValueCountFrequency (%)
-572
100.0%
Open Punctuation
ValueCountFrequency (%)
(39
100.0%
Close Punctuation
ValueCountFrequency (%)
)39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin202015
88.3%
Common26671
 
11.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i30297
15.0%
e19499
 
9.7%
a15535
 
7.7%
n15469
 
7.7%
v13084
 
6.5%
r11537
 
5.7%
o10997
 
5.4%
d9170
 
4.5%
t8291
 
4.1%
u7804
 
3.9%
Other values (38)60332
29.9%
Common
ValueCountFrequency (%)
12082
45.3%
/6734
25.2%
,2836
 
10.6%
11786
 
6.7%
21644
 
6.2%
-572
 
2.1%
0478
 
1.8%
.206
 
0.8%
3148
 
0.6%
582
 
0.3%
Other values (5)103
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII228686
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i30297
 
13.2%
e19499
 
8.5%
a15535
 
6.8%
n15469
 
6.8%
v13084
 
5.7%
12082
 
5.3%
r11537
 
5.0%
o10997
 
4.8%
d9170
 
4.0%
t8291
 
3.6%
Other values (53)82725
36.2%

brand
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Generic
7285 
Determine
799 
Uni-Gold
 
373
Aluvia
 
250
Kaletra
 
165
Other values (43)
1452 

Length

Max length15
Median length7
Mean length7.287969779
Min length3

Characters and Unicode

Total characters75241
Distinct characters48
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowReveal
2nd rowGeneric
3rd rowDetermine
4th rowGeneric
5th rowGeneric

Common Values

ValueCountFrequency (%)
Generic7285
70.6%
Determine799
 
7.7%
Uni-Gold373
 
3.6%
Aluvia250
 
2.4%
Kaletra165
 
1.6%
Norvir136
 
1.3%
Stat-Pak115
 
1.1%
Bioline113
 
1.1%
Truvada94
 
0.9%
Videx84
 
0.8%
Other values (38)910
 
8.8%

Length

2022-09-29T11:28:07.861974image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
generic7285
69.7%
determine799
 
7.6%
uni-gold373
 
3.6%
aluvia250
 
2.4%
kaletra165
 
1.6%
norvir136
 
1.3%
videx125
 
1.2%
stat-pak115
 
1.1%
bioline113
 
1.1%
truvada94
 
0.9%
Other values (40)995
 
9.5%

Most occurring characters

ValueCountFrequency (%)
e18044
24.0%
i10118
13.4%
r9288
12.3%
n8958
11.9%
G7758
10.3%
c7463
9.9%
t1628
 
2.2%
a1599
 
2.1%
l1331
 
1.8%
o991
 
1.3%
Other values (38)8063
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter63406
84.3%
Uppercase Letter11151
 
14.8%
Dash Punctuation489
 
0.6%
Space Separator126
 
0.2%
Other Punctuation69
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e18044
28.5%
i10118
16.0%
r9288
14.6%
n8958
14.1%
c7463
11.8%
t1628
 
2.6%
a1599
 
2.5%
l1331
 
2.1%
o991
 
1.6%
m856
 
1.4%
Other values (13)3130
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
G7758
69.6%
D804
 
7.2%
U373
 
3.3%
A271
 
2.4%
S259
 
2.3%
C227
 
2.0%
V222
 
2.0%
K167
 
1.5%
P163
 
1.5%
N141
 
1.3%
Other values (12)766
 
6.9%
Dash Punctuation
ValueCountFrequency (%)
-489
100.0%
Space Separator
ValueCountFrequency (%)
126
100.0%
Other Punctuation
ValueCountFrequency (%)
/69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin74557
99.1%
Common684
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e18044
24.2%
i10118
13.6%
r9288
12.5%
n8958
12.0%
G7758
10.4%
c7463
10.0%
t1628
 
2.2%
a1599
 
2.1%
l1331
 
1.8%
o991
 
1.3%
Other values (35)7379
9.9%
Common
ValueCountFrequency (%)
-489
71.5%
126
 
18.4%
/69
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII75241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e18044
24.0%
i10118
13.4%
r9288
12.3%
n8958
11.9%
G7758
10.3%
c7463
9.9%
t1628
 
2.2%
a1599
 
2.1%
l1331
 
1.8%
o991
 
1.3%
Other values (38)8063
10.7%

dosage
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct54
Distinct (%)0.6%
Missing1736
Missing (%)16.8%
Memory size80.8 KiB
300mg
990 
200mg
932 
600mg
772 
150/300mg
600 
150/300/200mg
580 
Other values (49)
4714 

Length

Max length15
Median length13
Mean length7.354448067
Min length2

Characters and Unicode

Total characters63160
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row10mg/ml
2nd row150mg
3rd row30mg
4th row10mg/ml
5th row200mg

Common Values

ValueCountFrequency (%)
300mg990
 
9.6%
200mg932
 
9.0%
600mg772
 
7.5%
150/300mg600
 
5.8%
150/300/200mg580
 
5.6%
10mg/ml552
 
5.3%
150mg431
 
4.2%
200/50mg395
 
3.8%
300/300mg301
 
2.9%
600/300/300mg286
 
2.8%
Other values (44)2749
26.6%
(Missing)1736
16.8%

Length

2022-09-29T11:28:07.990596image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
300mg990
 
11.5%
200mg932
 
10.9%
600mg772
 
9.0%
150/300mg600
 
7.0%
150/300/200mg580
 
6.8%
10mg/ml552
 
6.4%
150mg431
 
5.0%
200/50mg395
 
4.6%
300/300mg301
 
3.5%
600/300/300mg286
 
3.3%
Other values (44)2749
32.0%

Most occurring characters

ValueCountFrequency (%)
021765
34.5%
m9548
15.1%
g8596
 
13.6%
/6117
 
9.7%
34855
 
7.7%
23187
 
5.0%
13098
 
4.9%
53045
 
4.8%
61613
 
2.6%
l964
 
1.5%
Other values (4)372
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number37901
60.0%
Lowercase Letter19108
30.3%
Other Punctuation6131
 
9.7%
Math Symbol20
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
021765
57.4%
34855
 
12.8%
23187
 
8.4%
13098
 
8.2%
53045
 
8.0%
61613
 
4.3%
8171
 
0.5%
4167
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
m9548
50.0%
g8596
45.0%
l964
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/6117
99.8%
.14
 
0.2%
Math Symbol
ValueCountFrequency (%)
+20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common44052
69.7%
Latin19108
30.3%

Most frequent character per script

Common
ValueCountFrequency (%)
021765
49.4%
/6117
 
13.9%
34855
 
11.0%
23187
 
7.2%
13098
 
7.0%
53045
 
6.9%
61613
 
3.7%
8171
 
0.4%
4167
 
0.4%
+20
 
< 0.1%
Latin
ValueCountFrequency (%)
m9548
50.0%
g8596
45.0%
l964
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII63160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
021765
34.5%
m9548
15.1%
g8596
 
13.6%
/6117
 
9.7%
34855
 
7.7%
23187
 
5.0%
13098
 
4.9%
53045
 
4.8%
61613
 
2.6%
l964
 
1.5%
Other values (4)372
 
0.6%

dosage form
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Tablet
3532 
Tablet - FDC
2749 
Test kit
1575 
Capsule
729 
Oral solution
727 
Other values (12)
1012 

Length

Max length34
Median length33
Mean length10.25358388
Min length6

Characters and Unicode

Total characters105858
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowTest kit
2nd rowOral suspension
3rd rowTest kit
4th rowTablet
5th rowCapsule

Common Values

ValueCountFrequency (%)
Tablet3532
34.2%
Tablet - FDC2749
26.6%
Test kit1575
15.3%
Capsule729
 
7.1%
Oral solution727
 
7.0%
Chewable/dispersible tablet - FDC239
 
2.3%
Oral suspension214
 
2.1%
Test kit - Ancillary161
 
1.6%
Chewable/dispersible tablet146
 
1.4%
Delayed-release capsules131
 
1.3%
Other values (7)121
 
1.2%

Length

2022-09-29T11:28:08.114075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tablet6711
33.3%
3270
16.2%
fdc3023
15.0%
test1736
 
8.6%
kit1736
 
8.6%
oral970
 
4.8%
solution755
 
3.7%
capsule729
 
3.6%
chewable/dispersible385
 
1.9%
suspension214
 
1.1%
Other values (8)654
 
3.2%

Most occurring characters

ValueCountFrequency (%)
e12083
11.4%
t11415
10.8%
l10859
10.3%
9859
9.3%
a9472
8.9%
T8062
 
7.6%
b7567
 
7.1%
s5234
 
4.9%
C4137
 
3.9%
i3728
 
3.5%
Other values (22)23442
22.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter72598
68.6%
Uppercase Letter19554
 
18.5%
Space Separator9859
 
9.3%
Dash Punctuation3427
 
3.2%
Other Punctuation385
 
0.4%
Math Symbol35
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e12083
16.6%
t11415
15.7%
l10859
15.0%
a9472
13.0%
b7567
10.4%
s5234
7.2%
i3728
 
5.1%
u1870
 
2.6%
o1835
 
2.5%
r1831
 
2.5%
Other values (10)6704
9.2%
Uppercase Letter
ValueCountFrequency (%)
T8062
41.2%
C4137
21.2%
D3195
 
16.3%
F3023
 
15.5%
O942
 
4.8%
A161
 
0.8%
P28
 
0.1%
I6
 
< 0.1%
Space Separator
ValueCountFrequency (%)
9859
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3427
100.0%
Other Punctuation
ValueCountFrequency (%)
/385
100.0%
Math Symbol
ValueCountFrequency (%)
+35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin92152
87.1%
Common13706
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e12083
13.1%
t11415
12.4%
l10859
11.8%
a9472
10.3%
T8062
8.7%
b7567
8.2%
s5234
 
5.7%
C4137
 
4.5%
i3728
 
4.0%
D3195
 
3.5%
Other values (18)16400
17.8%
Common
ValueCountFrequency (%)
9859
71.9%
-3427
 
25.0%
/385
 
2.8%
+35
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII105858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e12083
11.4%
t11415
10.8%
l10859
10.3%
9859
9.3%
a9472
8.9%
T8062
 
7.6%
b7567
 
7.1%
s5234
 
4.9%
C4137
 
3.9%
i3728
 
3.5%
Other values (22)23442
22.1%

unit of measure (per pack)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.990895
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2022-09-29T11:28:08.224779image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20
Q130
median60
Q390
95-th percentile240
Maximum1000
Range999
Interquartile range (IQR)60

Descriptive statistics

Standard deviation76.57976396
Coefficient of variation (CV)0.9819064643
Kurtosis36.09399876
Mean77.990895
Median Absolute Deviation (MAD)30
Skewness4.302502487
Sum805178
Variance5864.460248
MonotonicityNot monotonic
2022-09-29T11:28:08.341465image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
604121
39.9%
302630
25.5%
100976
 
9.5%
240670
 
6.5%
120474
 
4.6%
20470
 
4.6%
90222
 
2.2%
300157
 
1.5%
1126
 
1.2%
25114
 
1.1%
Other values (21)364
 
3.5%
ValueCountFrequency (%)
1126
 
1.2%
24
 
< 0.1%
38
 
0.1%
54
 
< 0.1%
122
 
< 0.1%
184
 
< 0.1%
20470
 
4.6%
242
 
< 0.1%
25114
 
1.1%
302630
25.5%
ValueCountFrequency (%)
100016
 
0.2%
7205
 
< 0.1%
5407
 
0.1%
33639
 
0.4%
300157
 
1.5%
27053
 
0.5%
240670
6.5%
20076
 
0.7%
18076
 
0.7%
1683
 
< 0.1%

line item quantity
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5065
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18332.53487
Minimum1
Maximum619999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2022-09-29T11:28:08.468160image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17
Q1408
median3000
Q317039.75
95-th percentile90951.55
Maximum619999
Range619998
Interquartile range (IQR)16631.75

Descriptive statistics

Standard deviation40035.30296
Coefficient of variation (CV)2.18383891
Kurtosis40.0503001
Mean18332.53487
Median Absolute Deviation (MAD)2950
Skewness5.038314699
Sum189265090
Variance1602825483
MonotonicityNot monotonic
2022-09-29T11:28:08.598778image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000093
 
0.9%
100091
 
0.9%
10087
 
0.8%
200073
 
0.7%
500069
 
0.7%
50067
 
0.6%
2000067
 
0.6%
300066
 
0.6%
363
 
0.6%
5000062
 
0.6%
Other values (5055)9586
92.9%
ValueCountFrequency (%)
135
0.3%
240
0.4%
363
0.6%
446
0.4%
528
0.3%
648
0.5%
727
0.3%
826
0.3%
922
 
0.2%
1054
0.5%
ValueCountFrequency (%)
6199991
 
< 0.1%
6009061
 
< 0.1%
5551971
 
< 0.1%
5150003
< 0.1%
5145261
 
< 0.1%
4600411
 
< 0.1%
4400001
 
< 0.1%
4384091
 
< 0.1%
4019611
 
< 0.1%
4000002
< 0.1%

line item value
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct8741
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157650.5673
Minimum0
Maximum5951990.4
Zeros17
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2022-09-29T11:28:08.733418image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile192.5755
Q14314.5925
median30471.465
Q3166447.14
95-th percentile702831
Maximum5951990.4
Range5951990.4
Interquartile range (IQR)162132.5475

Descriptive statistics

Standard deviation345292.067
Coefficient of variation (CV)2.190236755
Kurtosis54.15243042
Mean157650.5673
Median Absolute Deviation (MAD)29920.465
Skewness5.837020186
Sum1627584457
Variance1.192266115 × 1011
MonotonicityNot monotonic
2022-09-29T11:28:08.862109image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000029
 
0.3%
1600023
 
0.2%
80018
 
0.2%
017
 
0.2%
1440016
 
0.2%
320015
 
0.1%
24421615
 
0.1%
12000013
 
0.1%
16011
 
0.1%
25011
 
0.1%
Other values (8731)10156
98.4%
ValueCountFrequency (%)
017
0.2%
0.011
 
< 0.1%
0.031
 
< 0.1%
0.121
 
< 0.1%
0.21
 
< 0.1%
0.241
 
< 0.1%
0.251
 
< 0.1%
0.421
 
< 0.1%
0.51
 
< 0.1%
0.71
 
< 0.1%
ValueCountFrequency (%)
5951990.41
< 0.1%
5768697.61
< 0.1%
5329891.21
< 0.1%
5140114.741
< 0.1%
4959241.981
< 0.1%
4278871.841
< 0.1%
4228629.721
< 0.1%
40140001
< 0.1%
39328801
< 0.1%
39040002
< 0.1%

pack price
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1175
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.91024119
Minimum0
Maximum1345.64
Zeros18
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2022-09-29T11:28:09.014700image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.9
Q14.12
median9.3
Q323.5925
95-th percentile80
Maximum1345.64
Range1345.64
Interquartile range (IQR)19.4725

Descriptive statistics

Standard deviation45.60922308
Coefficient of variation (CV)2.081639481
Kurtosis293.1762044
Mean21.91024119
Median Absolute Deviation (MAD)6.57
Skewness12.98843214
Sum226201.33
Variance2080.20123
MonotonicityNot monotonic
2022-09-29T11:28:09.158316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32368
 
3.6%
80307
 
3.0%
89183
 
1.8%
11.22139
 
1.3%
20110
 
1.1%
1.9591
 
0.9%
8.7691
 
0.9%
2.4490
 
0.9%
2.189
 
0.9%
2.2688
 
0.9%
Other values (1165)8768
84.9%
ValueCountFrequency (%)
018
 
0.2%
0.0185
0.8%
0.392
 
< 0.1%
0.72
 
< 0.1%
0.94
 
< 0.1%
1.12
 
< 0.1%
1.142
 
< 0.1%
1.171
 
< 0.1%
1.21
 
< 0.1%
1.211
 
< 0.1%
ValueCountFrequency (%)
1345.641
 
< 0.1%
12501
 
< 0.1%
1242.533
 
< 0.1%
750.291
 
< 0.1%
7001
 
< 0.1%
4009
 
0.1%
35039
0.4%
308.173
 
< 0.1%
306.883
 
< 0.1%
301.531
 
< 0.1%

unit price
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct183
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6117008911
Minimum0
Maximum238.65
Zeros103
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2022-09-29T11:28:09.295948image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.08
median0.16
Q30.47
95-th percentile1.6
Maximum238.65
Range238.65
Interquartile range (IQR)0.39

Descriptive statistics

Standard deviation3.275807741
Coefficient of variation (CV)5.35524435
Kurtosis2725.960252
Mean0.6117008911
Median Absolute Deviation (MAD)0.12
Skewness40.58484939
Sum6315.2
Variance10.73091635
MonotonicityNot monotonic
2022-09-29T11:28:09.431585image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.04713
 
6.9%
0.01492
 
4.8%
0.12464
 
4.5%
0.14444
 
4.3%
0.8411
 
4.0%
0.11400
 
3.9%
1.6368
 
3.6%
0.05343
 
3.3%
0.16343
 
3.3%
0.19321
 
3.1%
Other values (173)6025
58.4%
ValueCountFrequency (%)
0103
 
1.0%
0.01492
4.8%
0.02140
 
1.4%
0.03250
 
2.4%
0.04713
6.9%
0.05343
3.3%
0.06274
 
2.7%
0.07248
 
2.4%
0.08146
 
1.4%
0.09154
 
1.5%
ValueCountFrequency (%)
238.651
 
< 0.1%
41.681
 
< 0.1%
37.52
 
< 0.1%
301
 
< 0.1%
26.911
 
< 0.1%
254
 
< 0.1%
24.853
 
< 0.1%
24.546
0.4%
2323
0.2%
17.123
 
< 0.1%

manufacturing site
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct88
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Aurobindo Unit III, India
3172 
Mylan (formerly Matrix) Nashik
1415 
Hetero Unit III Hyderabad IN
869 
Cipla, Goa, India
665 
Strides, Bangalore, India.
540 
Other values (83)
3663 

Length

Max length72
Median length37
Mean length25.03913212
Min length5

Characters and Unicode

Total characters258504
Distinct characters69
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.2%

Sample

1st rowRanbaxy Fine Chemicals LTD
2nd rowAurobindo Unit III, India
3rd rowABBVIE GmbH & Co.KG Wiesbaden
4th rowRanbaxy, Paonta Shahib, India
5th rowAurobindo Unit III, India

Common Values

ValueCountFrequency (%)
Aurobindo Unit III, India3172
30.7%
Mylan (formerly Matrix) Nashik1415
13.7%
Hetero Unit III Hyderabad IN869
 
8.4%
Cipla, Goa, India665
 
6.4%
Strides, Bangalore, India.540
 
5.2%
Alere Medical Co., Ltd.481
 
4.7%
Trinity Biotech, Plc405
 
3.9%
ABBVIE Ludwigshafen Germany366
 
3.5%
Inverness Japan345
 
3.3%
ABBVIE (Abbott) Logis. UK219
 
2.1%
Other values (78)1847
17.9%

Length

2022-09-29T11:28:09.568257image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
india4678
 
11.9%
unit4197
 
10.7%
iii4041
 
10.3%
aurobindo3283
 
8.4%
mylan1438
 
3.7%
formerly1415
 
3.6%
matrix1415
 
3.6%
nashik1415
 
3.6%
in1047
 
2.7%
hetero913
 
2.3%
Other values (201)15396
39.2%

Most occurring characters

ValueCountFrequency (%)
28937
 
11.2%
i20789
 
8.0%
I19607
 
7.6%
a18921
 
7.3%
n18236
 
7.1%
r13636
 
5.3%
o12958
 
5.0%
d12314
 
4.8%
e10570
 
4.1%
t10195
 
3.9%
Other values (59)92341
35.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter160634
62.1%
Uppercase Letter53461
 
20.7%
Space Separator28937
 
11.2%
Other Punctuation11140
 
4.3%
Close Punctuation1827
 
0.7%
Open Punctuation1827
 
0.7%
Dash Punctuation435
 
0.2%
Decimal Number242
 
0.1%
Modifier Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i20789
12.9%
a18921
11.8%
n18236
11.4%
r13636
8.5%
o12958
8.1%
d12314
 
7.7%
e10570
 
6.6%
t10195
 
6.3%
l6416
 
4.0%
b5385
 
3.4%
Other values (16)31214
19.4%
Uppercase Letter
ValueCountFrequency (%)
I19607
36.7%
A5146
 
9.6%
U4492
 
8.4%
M4127
 
7.7%
B2746
 
5.1%
N2729
 
5.1%
H2130
 
4.0%
S1830
 
3.4%
C1732
 
3.2%
G1371
 
2.6%
Other values (14)7551
 
14.1%
Decimal Number
ValueCountFrequency (%)
296
39.7%
154
22.3%
544
18.2%
326
 
10.7%
417
 
7.0%
72
 
0.8%
61
 
0.4%
91
 
0.4%
01
 
0.4%
Other Punctuation
ValueCountFrequency (%)
,8728
78.3%
.2314
 
20.8%
&66
 
0.6%
'28
 
0.3%
/4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
28937
100.0%
Close Punctuation
ValueCountFrequency (%)
)1827
100.0%
Open Punctuation
ValueCountFrequency (%)
(1827
100.0%
Dash Punctuation
ValueCountFrequency (%)
-435
100.0%
Modifier Symbol
ValueCountFrequency (%)
¸1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin214095
82.8%
Common44409
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i20789
 
9.7%
I19607
 
9.2%
a18921
 
8.8%
n18236
 
8.5%
r13636
 
6.4%
o12958
 
6.1%
d12314
 
5.8%
e10570
 
4.9%
t10195
 
4.8%
l6416
 
3.0%
Other values (40)70453
32.9%
Common
ValueCountFrequency (%)
28937
65.2%
,8728
 
19.7%
.2314
 
5.2%
)1827
 
4.1%
(1827
 
4.1%
-435
 
1.0%
296
 
0.2%
&66
 
0.1%
154
 
0.1%
544
 
0.1%
Other values (9)81
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII258502
> 99.9%
Latin 1 Sup2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28937
 
11.2%
i20789
 
8.0%
I19607
 
7.6%
a18921
 
7.3%
n18236
 
7.1%
r13636
 
5.3%
o12958
 
5.0%
d12314
 
4.8%
e10570
 
4.1%
t10195
 
3.9%
Other values (57)92339
35.7%
Latin 1 Sup
ValueCountFrequency (%)
Ã1
50.0%
¸1
50.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
True
7030 
False
3294 
ValueCountFrequency (%)
True7030
68.1%
False3294
31.9%
2022-09-29T11:28:09.693916image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

weight (kilograms)
Categorical

HIGH CARDINALITY

Distinct4688
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Weight Captured Separately
1507 
2
 
29
6
 
26
1
 
23
5
 
20
Other values (4683)
8719 

Length

Max length26
Median length24
Mean length11.35916312
Min length1

Characters and Unicode

Total characters117272
Distinct characters35
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3014 ?
Unique (%)29.2%

Sample

1st row13
2nd row358
3rd row171
4th row1855
5th row7590

Common Values

ValueCountFrequency (%)
Weight Captured Separately1507
 
14.6%
229
 
0.3%
626
 
0.3%
123
 
0.2%
520
 
0.2%
6020
 
0.2%
419
 
0.2%
318
 
0.2%
3917
 
0.2%
917
 
0.2%
Other values (4678)8628
83.6%

Length

2022-09-29T11:28:09.785672image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
see2445
 
13.4%
weight1507
 
8.3%
separately1507
 
8.3%
captured1507
 
8.3%
229
 
0.2%
626
 
0.1%
123
 
0.1%
520
 
0.1%
6020
 
0.1%
419
 
0.1%
Other values (5980)11125
61.0%

Most occurring characters

ValueCountFrequency (%)
e10918
 
9.3%
7904
 
6.7%
16455
 
5.5%
25833
 
5.0%
35113
 
4.4%
84534
 
3.9%
t4521
 
3.9%
a4521
 
3.9%
S4460
 
3.8%
D4382
 
3.7%
Other values (25)58631
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number43352
37.0%
Lowercase Letter36537
31.2%
Uppercase Letter17254
 
14.7%
Space Separator7904
 
6.7%
Other Punctuation4890
 
4.2%
Open Punctuation2445
 
2.1%
Close Punctuation2445
 
2.1%
Dash Punctuation2445
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e10918
29.9%
t4521
12.4%
a4521
12.4%
r3014
 
8.2%
p3014
 
8.2%
y1507
 
4.1%
l1507
 
4.1%
d1507
 
4.1%
u1507
 
4.1%
h1507
 
4.1%
Other values (2)3014
 
8.2%
Decimal Number
ValueCountFrequency (%)
16455
14.9%
25833
13.5%
35113
11.8%
84534
10.5%
44073
9.4%
53786
8.7%
03559
8.2%
63541
8.2%
73309
7.6%
93149
7.3%
Uppercase Letter
ValueCountFrequency (%)
S4460
25.8%
D4382
25.4%
N2445
14.2%
I2445
14.2%
W1507
 
8.7%
C1507
 
8.7%
A508
 
2.9%
Other Punctuation
ValueCountFrequency (%)
#2445
50.0%
:2445
50.0%
Space Separator
ValueCountFrequency (%)
7904
100.0%
Open Punctuation
ValueCountFrequency (%)
(2445
100.0%
Close Punctuation
ValueCountFrequency (%)
)2445
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common63481
54.1%
Latin53791
45.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e10918
20.3%
t4521
 
8.4%
a4521
 
8.4%
S4460
 
8.3%
D4382
 
8.1%
r3014
 
5.6%
p3014
 
5.6%
N2445
 
4.5%
I2445
 
4.5%
W1507
 
2.8%
Other values (9)12564
23.4%
Common
ValueCountFrequency (%)
7904
12.5%
16455
10.2%
25833
 
9.2%
35113
 
8.1%
84534
 
7.1%
44073
 
6.4%
53786
 
6.0%
03559
 
5.6%
63541
 
5.6%
73309
 
5.2%
Other values (6)15374
24.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII117272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e10918
 
9.3%
7904
 
6.7%
16455
 
5.5%
25833
 
5.0%
35113
 
4.4%
84534
 
3.9%
t4521
 
3.9%
a4521
 
3.9%
S4460
 
3.8%
D4382
 
3.7%
Other values (25)58631
50.0%

freight cost (usd)
Categorical

HIGH CARDINALITY

Distinct6733
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size80.8 KiB
Freight Included in Commodity Cost
1442 
Invoiced Separately
 
239
9736.1
 
36
6147.18
 
27
See DN-304 (ID#:10589)
 
16
Other values (6728)
8564 

Length

Max length34
Median length24
Mean length14.79523441
Min length2

Characters and Unicode

Total characters152746
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5849 ?
Unique (%)56.7%

Sample

1st row780.34
2nd row4521.5
3rd row1653.78
4th row16007.06
5th row45450.08

Common Values

ValueCountFrequency (%)
Freight Included in Commodity Cost1442
 
14.0%
Invoiced Separately239
 
2.3%
9736.136
 
0.3%
6147.1827
 
0.3%
See DN-304 (ID#:10589)16
 
0.2%
7445.816
 
0.2%
13398.0616
 
0.2%
9341.4915
 
0.1%
See ASN-32231 (ID#:13648)14
 
0.1%
See ASN-31750 (ID#:19272)14
 
0.1%
Other values (6723)8489
82.2%

Length

2022-09-29T11:28:09.899370image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
see2445
 
11.5%
freight1442
 
6.8%
in1442
 
6.8%
commodity1442
 
6.8%
cost1442
 
6.8%
included1442
 
6.8%
invoiced239
 
1.1%
separately239
 
1.1%
9736.136
 
0.2%
6147.1827
 
0.1%
Other values (8028)11025
52.0%

Most occurring characters

ValueCountFrequency (%)
10897
 
7.1%
e8491
 
5.6%
18391
 
5.5%
27344
 
4.8%
36673
 
4.4%
86162
 
4.0%
.5734
 
3.8%
45646
 
3.7%
55346
 
3.5%
65136
 
3.4%
Other values (32)82926
54.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number58705
38.4%
Lowercase Letter46206
30.3%
Uppercase Letter18979
 
12.4%
Space Separator10897
 
7.1%
Other Punctuation10624
 
7.0%
Open Punctuation2445
 
1.6%
Dash Punctuation2445
 
1.6%
Close Punctuation2445
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e8491
18.4%
t4565
9.9%
d4565
9.9%
o4565
9.9%
i4565
9.9%
n3123
 
6.8%
m2884
 
6.2%
r1681
 
3.6%
y1681
 
3.6%
l1681
 
3.6%
Other values (8)8405
18.2%
Decimal Number
ValueCountFrequency (%)
18391
14.3%
27344
12.5%
36673
11.4%
86162
10.5%
45646
9.6%
55346
9.1%
65136
8.7%
94752
8.1%
74746
8.1%
04509
7.7%
Uppercase Letter
ValueCountFrequency (%)
D4382
23.1%
I4126
21.7%
S3192
16.8%
C2884
15.2%
N2445
12.9%
F1442
 
7.6%
A508
 
2.7%
Other Punctuation
ValueCountFrequency (%)
.5734
54.0%
#2445
23.0%
:2445
23.0%
Space Separator
ValueCountFrequency (%)
10897
100.0%
Open Punctuation
ValueCountFrequency (%)
(2445
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2445
100.0%
Close Punctuation
ValueCountFrequency (%)
)2445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common87561
57.3%
Latin65185
42.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e8491
13.0%
t4565
 
7.0%
d4565
 
7.0%
o4565
 
7.0%
i4565
 
7.0%
D4382
 
6.7%
I4126
 
6.3%
S3192
 
4.9%
n3123
 
4.8%
m2884
 
4.4%
Other values (15)20727
31.8%
Common
ValueCountFrequency (%)
10897
12.4%
18391
 
9.6%
27344
 
8.4%
36673
 
7.6%
86162
 
7.0%
.5734
 
6.5%
45646
 
6.4%
55346
 
6.1%
65136
 
5.9%
94752
 
5.4%
Other values (7)21480
24.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII152746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10897
 
7.1%
e8491
 
5.6%
18391
 
5.5%
27344
 
4.8%
36673
 
4.4%
86162
 
4.0%
.5734
 
3.8%
45646
 
3.7%
55346
 
3.5%
65136
 
3.4%
Other values (32)82926
54.3%

line item insurance (usd)
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6722
Distinct (%)67.0%
Missing287
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean240.1176258
Minimum0
Maximum7708.44
Zeros54
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2022-09-29T11:28:10.021045image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.25
Q16.51
median47.04
Q3252.4
95-th percentile1082.032
Maximum7708.44
Range7708.44
Interquartile range (IQR)245.89

Descriptive statistics

Standard deviation500.1905677
Coefficient of variation (CV)2.083106419
Kurtosis34.91121486
Mean240.1176258
Median Absolute Deviation (MAD)46.27
Skewness4.827162374
Sum2410060.61
Variance250190.604
MonotonicityNot monotonic
2022-09-29T11:28:10.277354image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
054
 
0.5%
0.0237
 
0.4%
0.0733
 
0.3%
0.0530
 
0.3%
0.0630
 
0.3%
0.0126
 
0.3%
0.0323
 
0.2%
0.0921
 
0.2%
0.0820
 
0.2%
0.4918
 
0.2%
Other values (6712)9745
94.4%
(Missing)287
 
2.8%
ValueCountFrequency (%)
054
0.5%
0.0126
0.3%
0.0237
0.4%
0.0323
0.2%
0.0414
 
0.1%
0.0530
0.3%
0.0630
0.3%
0.0733
0.3%
0.0820
 
0.2%
0.0921
 
0.2%
ValueCountFrequency (%)
7708.441
< 0.1%
7005.491
< 0.1%
5930.221
< 0.1%
5573.311
< 0.1%
5479.131
< 0.1%
5284.041
< 0.1%
5230.811
< 0.1%
5162.291
< 0.1%
51452
< 0.1%
5098.11
< 0.1%

Interactions

2022-09-29T11:28:01.443671image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:54.677335image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:55.901062image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.008728image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.927268image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:58.887702image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:00.408411image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:01.566341image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:54.862839image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:56.077588image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.123418image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:58.066894image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:59.041289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:00.554052image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:01.702975image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:55.002469image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:56.311607image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.256064image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:58.192558image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:59.373540image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:00.702654image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:01.835621image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:55.153100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:56.472163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.385717image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:58.318221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:59.575385image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:00.862231image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:02.001212image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:55.301664image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:56.610791image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.515413image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:58.467820image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:59.743938image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:00.995869image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:02.137846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:55.619815image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:56.742438image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.642032image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:58.598470image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:00.037441image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:01.130511image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:02.271491image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:55.766419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:56.873091image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:57.785648image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:27:58.741089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:00.223904image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-09-29T11:28:01.258171image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-09-29T11:28:10.395006image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-29T11:28:10.562341image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-29T11:28:10.718920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-29T11:28:10.896451image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-09-29T11:28:11.097905image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-29T11:28:02.581684image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-09-29T11:28:03.752522image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-29T11:28:04.075857image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-29T11:28:04.236935image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idproject codepq #po / so #asn/dn #countrymanaged byfulfill viavendor inco termshipment modepq first sent to client datepo sent to vendor datescheduled delivery datedelivered to client datedelivery recorded dateproduct groupsub classificationvendoritem descriptionmolecule/test typebranddosagedosage formunit of measure (per pack)line item quantityline item valuepack priceunit pricemanufacturing sitefirst line designationweight (kilograms)freight cost (usd)line item insurance (usd)
01100-CI-T01Pre-PQ ProcessSCMS-4ASN-8Côte d'IvoirePMO - USDirect DropEXWAirPre-PQ ProcessDate Not Captured2-Jun-062-Jun-062-Jun-06HRDTHIV testRANBAXY Fine Chemicals LTD.HIV, Reveal G3 Rapid HIV-1 Antibody Test, 30 TestsHIV, Reveal G3 Rapid HIV-1 Antibody TestRevealNaNTest kit3019551.0029.000.97Ranbaxy Fine Chemicals LTDTrue13780.34NaN
13108-VN-T01Pre-PQ ProcessSCMS-13ASN-85VietnamPMO - USDirect DropEXWAirPre-PQ ProcessDate Not Captured14-Nov-0614-Nov-0614-Nov-06ARVPediatricAurobindo Pharma LimitedNevirapine 10mg/ml, oral suspension, Bottle, 240 mlNevirapineGeneric10mg/mlOral suspension24010006200.006.200.03Aurobindo Unit III, IndiaTrue3584521.5NaN
24100-CI-T01Pre-PQ ProcessSCMS-20ASN-14Côte d'IvoirePMO - USDirect DropFCAAirPre-PQ ProcessDate Not Captured27-Aug-0627-Aug-0627-Aug-06HRDTHIV testAbbott GmbH & Co. KGHIV 1/2, Determine Complete HIV Kit, 100 TestsHIV 1/2, Determine Complete HIV KitDetermineNaNTest kit10050040000.0080.000.80ABBVIE GmbH & Co.KG WiesbadenTrue1711653.78NaN
315108-VN-T01Pre-PQ ProcessSCMS-78ASN-50VietnamPMO - USDirect DropEXWAirPre-PQ ProcessDate Not Captured1-Sep-061-Sep-061-Sep-06ARVAdultSUN PHARMACEUTICAL INDUSTRIES LTD (RANBAXY LABORATORIES LIMITED)Lamivudine 150mg, tablets, 60 TabsLamivudineGeneric150mgTablet6031920127360.803.990.07Ranbaxy, Paonta Shahib, IndiaTrue185516007.06NaN
416108-VN-T01Pre-PQ ProcessSCMS-81ASN-55VietnamPMO - USDirect DropEXWAirPre-PQ ProcessDate Not Captured11-Aug-0611-Aug-0611-Aug-06ARVAdultAurobindo Pharma LimitedStavudine 30mg, capsules, 60 CapsStavudineGeneric30mgCapsule6038000121600.003.200.05Aurobindo Unit III, IndiaTrue759045450.08NaN
523112-NG-T01Pre-PQ ProcessSCMS-87ASN-57NigeriaPMO - USDirect DropEXWAirPre-PQ ProcessDate Not Captured28-Sep-0628-Sep-0628-Sep-06ARVPediatricAurobindo Pharma LimitedZidovudine 10mg/ml, oral solution, Bottle, 240 mlZidovudineGeneric10mg/mlOral solution2404162225.605.350.02Aurobindo Unit III, IndiaTrue5045920.42NaN
644110-ZM-T01Pre-PQ ProcessSCMS-139ASN-130ZambiaPMO - USDirect DropDDUAirPre-PQ ProcessDate Not Captured8-Jan-078-Jan-078-Jan-07ARVPediatricMERCK SHARP & DOHME IDEA GMBH (FORMALLY MERCK SHARP & DOHME B.V.)Efavirenz 200mg [Stocrin/Sustiva], capsule, 90 CapsEfavirenzStocrin/Sustiva200mgCapsule901354374.0032.400.36MSD South Granville AustraliaTrue328Freight Included in Commodity CostNaN
745109-TZ-T01Pre-PQ ProcessSCMS-140ASN-94TanzaniaPMO - USDirect DropEXWAirPre-PQ ProcessDate Not Captured24-Nov-0624-Nov-0624-Nov-06ARVAdultAurobindo Pharma LimitedNevirapine 200mg, tablets, 60 TabsNevirapineGeneric200mgTablet601666760834.553.650.06Aurobindo Unit III, IndiaTrue14786212.41NaN
846112-NG-T01Pre-PQ ProcessSCMS-156ASN-93NigeriaPMO - USDirect DropEXWAirPre-PQ ProcessDate Not Captured7-Dec-067-Dec-067-Dec-06ARVAdultAurobindo Pharma LimitedStavudine 30mg, capsules, 60 CapsStavudineGeneric30mgCapsule60273532.351.950.03Aurobindo Unit III, IndiaFalseSee ASN-93 (ID#:1281)See ASN-93 (ID#:1281)NaN
947110-ZM-T01Pre-PQ ProcessSCMS-165ASN-199ZambiaPMO - USDirect DropCIPAirPre-PQ Process11/13/200630-Jan-0730-Jan-0730-Jan-07ARVAdultABBVIE LOGISTICS (FORMERLY ABBOTT LOGISTICS BV)Lopinavir/Ritonavir 200/50mg [Aluvia], tablets, 120 TabsLopinavir/RitonavirAluvia200/50mgTablet1202800115080.0041.100.34ABBVIE (Abbott) St. P'burg USATrue643Freight Included in Commodity CostNaN

Last rows

idproject codepq #po / so #asn/dn #countrymanaged byfulfill viavendor inco termshipment modepq first sent to client datepo sent to vendor datescheduled delivery datedelivered to client datedelivery recorded dateproduct groupsub classificationvendoritem descriptionmolecule/test typebranddosagedosage formunit of measure (per pack)line item quantityline item valuepack priceunit pricemanufacturing sitefirst line designationweight (kilograms)freight cost (usd)line item insurance (usd)
1031486813151-NG-T30FPQ-14989SO-51422DN-4274NigeriaPMO - USFrom RDCN/A - From RDCAir Charter9/19/2014N/A - From RDC30-Jun-1515-May-1522-May-15ARVPediatricSCMS from RDCLamivudine/Nevirapine/Zidovudine 30/50/60mg, dispersible tablets, 60 TabsLamivudine/Nevirapine/ZidovudineGeneric30/50/60mgChewable/dispersible tablet - FDC601034037224.003.600.06Mylan (formerly Matrix) NashikFalseSee DN-4274 (ID#:84472)See DN-4274 (ID#:84472)38.27
1031586814151-NG-T30FPQ-14989SO-51424DN-4276NigeriaPMO - USFrom RDCN/A - From RDCAir Charter9/19/2014N/A - From RDC30-Jun-1515-May-1522-May-15ARVAdultSCMS from RDCLopinavir/Ritonavir 200/50mg [Aluvia], tablets, 120 TabsLopinavir/RitonavirAluvia200/50mgTablet120700001304800.0018.640.16ABBVIE Ludwigshafen GermanyTrue15198261801341.33
1031686815151-NG-T30FPQ-16313SO-51420DN-4279NigeriaPMO - USFrom RDCN/A - From RDCAir Charter5/4/2015N/A - From RDC2-Jun-1515-May-1522-May-15ARVAdultSCMS from RDCLamivudine/Zidovudine 150/300mg, tablets, 60 TabsLamivudine/ZidovudineGeneric150/300mgTablet - FDC601500097800.006.520.11Aurobindo Unit III, IndiaTrue15473410115.11
1031786816151-NG-T30FPQ-16313SO-51440DN-4282NigeriaPMO - USFrom RDCN/A - From RDCAir5/4/2015N/A - From RDC30-Jun-1522-Jun-1529-Jun-15ARVAdultSCMS from RDCEfavirenz 600mg, tablets, 30 TabsEfavirenzGeneric600mgTablet30672420978.883.120.10Strides, Bangalore, India.FalseSee DN-4282 (ID#:83919)See DN-4282 (ID#:83919)24.69
1031886817103-ZW-T30FPQ-15197SO-50020DN-4307ZimbabwePMO - USFrom RDCN/A - From RDCTruck10/16/2014N/A - From RDC31-Jul-1515-Jul-1520-Jul-15ARVPediatricSCMS from RDCLamivudine/Nevirapine/Zidovudine 30/50/60mg, dispersible tablets, 60 TabsLamivudine/Nevirapine/ZidovudineGeneric30/50/60mgChewable/dispersible tablet - FDC60205243738874.803.600.06Cipla, Goa, IndiaFalseSee DN-4307 (ID#:83920)See DN-4307 (ID#:83920)869.66
1031986818103-ZW-T30FPQ-15197SO-50020DN-4307ZimbabwePMO - USFrom RDCN/A - From RDCTruck10/16/2014N/A - From RDC31-Jul-1515-Jul-1520-Jul-15ARVPediatricSCMS from RDCLamivudine/Nevirapine/Zidovudine 30/50/60mg, dispersible tablets, 60 TabsLamivudine/Nevirapine/ZidovudineGeneric30/50/60mgChewable/dispersible tablet - FDC60166571599655.603.600.06Mylan, H-12 & H-13, IndiaFalseSee DN-4307 (ID#:83920)See DN-4307 (ID#:83920)705.79
1032086819104-CI-T30FPQ-15259SO-50102DN-4313Côte d'IvoirePMO - USFrom RDCN/A - From RDCTruck10/24/2014N/A - From RDC31-Jul-156-Aug-157-Aug-15ARVAdultSCMS from RDCLamivudine/Zidovudine 150/300mg, tablets, 60 TabsLamivudine/ZidovudineGeneric150/300mgTablet - FDC6021072137389.446.520.11Hetero Unit III Hyderabad INFalseSee DN-4313 (ID#:83921)See DN-4313 (ID#:83921)161.71
1032186821110-ZM-T30FPQ-14784SO-49600DN-4316ZambiaPMO - USFrom RDCN/A - From RDCTruck8/12/2014N/A - From RDC31-Aug-1525-Aug-153-Sep-15ARVAdultSCMS from RDCEfavirenz/Lamivudine/Tenofovir Disoproxil Fumarate 600/300/300mg, tablets, 30 TabsEfavirenz/Lamivudine/Tenofovir Disoproxil FumarateGeneric600/300/300mgTablet - FDC305145265140114.749.990.33Cipla Ltd A-42 MIDC Mahar. INFalseWeight Captured SeparatelyFreight Included in Commodity Cost5284.04
1032286822200-ZW-T30FPQ-16523SO-51680DN-4334ZimbabwePMO - USFrom RDCN/A - From RDCTruck7/1/2015N/A - From RDC9-Sep-154-Aug-1511-Aug-15ARVAdultSCMS from RDCLamivudine/Zidovudine 150/300mg, tablets, 60 TabsLamivudine/ZidovudineGeneric150/300mgTablet - FDC6017465113871.806.520.11Mylan (formerly Matrix) NashikTrue1392Freight Included in Commodity Cost134.03
1032386823103-ZW-T30FPQ-15197SO-50022DN-4336ZimbabwePMO - USFrom RDCN/A - From RDCTruck10/16/2014N/A - From RDC31-Aug-154-Aug-1511-Aug-15ARVPediatricSCMS from RDCLamivudine/Zidovudine 30/60mg, dispersible tablets, 60 TabsLamivudine/ZidovudineGeneric30/60mgChewable/dispersible tablet - FDC603663972911.611.990.03Cipla, Goa, IndiaFalseWeight Captured SeparatelyFreight Included in Commodity Cost85.82